Patent Grant
10448185
Embodiments according to the invention are related to a multi-channel decorrelator for providing a plurality of decorrelated signals on the basis of a plurality of decorrelator input signals.
Further embodiments according to the invention are related to a multi-channel audio decoder for providing at least two output audio signals on the basis of an encoded representation.
Further embodiments according to the invention are related to a multi-channel audio encoder for providing an encoded representation on the basis of at least two input audio signals.
Further embodiments according to the invention are related to a method for providing a plurality of decorrelated signals on the basis of a plurality of decorrelator input signals.
Some embodiments according to the invention are related to a method for providing at least two output audio signals on the basis of an encoded representation.
Some embodiments according to the invention are related to a method for providing an encoded representation on the basis of at least two input audio signals.
Some embodiments according to the invention are related to a computer program for performing one of said methods.
Some embodiments according to the invention are related to an encoded audio representation.
Generally speaking, some embodiments according to the invention are related to a decorrelation concept for multi-channel downmix/upmix parametric audio object coding systems.
In recent years, demand for storage and transmission of audio contents has steadily increased. Moreover, the quality requirements for the storage and transmission of audio contents have also steadily increased. Accordingly, the concepts for the encoding and decoding of audio content have been enhanced.
For example, the so called “Advanced Audio Coding” (AAC) has been developed, which is described, for example, in the international standard ISO/IEC 13818-7:2003. Moreover, some spatial extensions have been created, like for example the so called “MPEG Surround” concept, which is described, for example, in the international standard ISO/IEC 23003-1:2007. Moreover, additional improvements for encoding and decoding of spatial information of audio signals are described in the international standard ISO/IEC 23003-2:2010, which relates to the so called “Spatial Audio Object Coding”.
Moreover, a switchable audio encoding/decoding concept which provides the possibility to encode both general audio signals and speech signals with good coding efficiency and to handle multi-channel audio signals is defined in the international standard ISO/IEC 23003-3:2012, which describes the so called “Unified Speech and Audio Coding” concept.
Moreover, further conventional concepts are described in the references, which are mentioned at the end of the present description.
However, there is a desire to provide an even more advanced concept for an efficient coding and decoding of 3-dimensional audio scenes.
An embodiment may have a multi-channel decorrelator for providing a plurality of decorrelated signals on the basis of a plurality of decorrelator input signals,
wherein the multi-channel decorrelator is configured to premix a first set of N decorrelator input signals into a second set of K decorrelator input signals, wherein K<N;
wherein the multi-channel decorrelator is configured to provide a first set of K′ decorrelator output signals on the basis of the second set of K decorrelator input signals; and
wherein the multi-channel decorrelator is configured to upmix the first set of K′ decorrelator output signals into a second set of N′ decorrelator output signals, wherein N′>K′;
wherein the multi-channel decorrelator is configured to premix the first set {circumflex over (Z)} of N decorrelator input signals into the second set {circumflex over (Z)}mix of K decorrelator input signals using a premixing matrix Mpre according to
{circumflex over (Z)}mix=Mpre{circumflex over (Z)}
wherein the multi-channel decorrelator is configured to obtain the first set {circumflex over (Z)}mixdec of K′ decorrelator output signals on the basis of the second set {circumflex over (Z)}mix of K decorrelator input signals, and
wherein the multi-channel decorrelator is configured to upmix the first set {circumflex over (Z)}mixdec of K′ decorrelator output signals into the second set W of N′ decorrelator output signals using a postmixing matrix Mpost according to
W=Mpost{circumflex over (Z)}mixdec,
wherein the multi-channel decorrelator is configured to select the premixing matrix Mpre in dependence on spatial positions to which the channel signals of the first set {circumflex over (Z)} of N decorrelator input signals are associated.
Another embodiment may have a multi-channel audio decoder for providing at least two output audio signals on the basis of an encoded representation,
wherein the multi-channel audio decoder has a multi-channel decorrelator as mentioned above.
Another embodiment may have a multi-channel audio encoder for providing an encoded representation on the basis of at least two input audio signals,
wherein the multi-channel audio encoder is configured to provide one or more downmix signals on the basis of the at least two input audio signals, and
wherein the multi-channel audio encoder is configured to provide one or more parameters describing a relationship between the at least two input audio signals, and
wherein the multi-channel audio encoder is configured to provide a decorrelation complexity parameter describing a complexity of a decorrelation to be used at the side of an audio decoder.
According to another embodiment, a method for providing a plurality of decorrelated signals on the basis of a plurality of decorrelator input signals may have the steps of:
premixing a first set of N decorrelator input signals into a second set of K decorrelator input signals, wherein K<N;
providing a first set of K′ decorrelator output signals on the basis of the second set of K decorrelator input signals; and
upmixing the first set of K′ decorrelator output signals into a second set of N′ decorrelator output signals, wherein N′>K′.
wherein the first set {circumflex over (Z)} of N decorrelator input signals is premixed into the second set {circumflex over (Z)}mix of K decorrelator input signals using a premixing matrix Mpre according to
{circumflex over (Z)}mix=Mpre{circumflex over (Z)}
wherein the first set {circumflex over (Z)}mixdec of K′ decorrelator output signals is obtained on the basis of the second set {circumflex over (Z)}mix of K decorrelator input signals, and
wherein the first set {circumflex over (Z)}mixdec of K′ decorrelator output signals is upmixed into the second set W of N′ decorrelator output signals using a postmixing matrix Mpost according to
W=Mpost{circumflex over (Z)}mixdec,
wherein the premixing matrix Mpre is selected in dependence on spatial positions to which the channel signals of the first set {circumflex over (Z)} of N decorrelator input signals are associated
Another embodiment may have a method for providing at least two output audio signals on the basis of an encoded representation,
wherein the method has providing a plurality of decorrelated signals on the basis of a plurality of decorrelator input signals as mentioned above.
According to another embodiment, a method for providing an encoded representation on the basis of at least two input audio signals may have the steps of:
providing one or more downmix signals on the basis of the at least two input audio signals, and
providing one or more parameters describing a relationship between the at least two input audio signals, and
providing a decorrelation complexity parameter describing a complexity of a decorrelation to be used at the side of an audio decoder.
Another embodiment may have a computer program for performing the above methods when the computer program runs on a computer.
According to another embodiment, an encoded audio representation may have:
an encoded representation of a downmix signal;
an encoded representation of one or more parameters describing a relationship between the at least two input audio signals, and
an encoded decorrelation complexity parameter describing a complexity of a decorrelation to be used at the side of an audio decoder.
Still another embodiment may have a multi-channel decorrelator for providing a plurality of decorrelated signals on the basis of a plurality of decorrelator input signals,
wherein the multi-channel decorrelator is configured to premix a first set of N decorrelator input signals into a second set of K decorrelator input signals, wherein K<N;
wherein the multi-channel decorrelator is configured to provide a first set of K′ decorrelator output signals on the basis of the second set of K decorrelator input signals; and
wherein the multi-channel decorrelator is configured to upmix the first set of K′ decorrelator output signals into a second set of N′ decorrelator output signals, wherein N′>K′;
wherein the multi-channel decorrelator is configured to premix the first set {circumflex over (Z)} of N decorrelator input signals into the second set {circumflex over (Z)}mix of K decorrelator input signals using a premixing matrix Mpre according to
{circumflex over (Z)}mix=Mpre{circumflex over (Z)}
wherein the multi-channel decorrelator is configured to obtain the first set {circumflex over (Z)}mixdec of K′ decorrelator output signals on the basis of the second set {circumflex over (Z)}mix of K decorrelator input signals, and
wherein the multi-channel decorrelator is configured to upmix the first set {circumflex over (Z)}mix of K′ decorrelator output signals into the second set W of N′ decorrelator output signals using a postmixing matrix Mpost according to
W=Mpost{circumflex over (Z)}mixdec;
wherein the multi-channel decorrelator is configured to select the premixing matrix Mpre in dependence on correlation characteristics or covariance characteristics of the channel signals of the first set {circumflex over (Z)} of N decorrelator input signals.
Another embodiment may have a multi-channel decorrelator for providing a plurality of decorrelated signals on the basis of a plurality of decorrelator input signals,
wherein the multi-channel decorrelator is configured to premix a first set of N decorrelator input signals into a second set of K decorrelator input signals, wherein K<N;
wherein the multi-channel decorrelator is configured to provide a first set of K′ decorrelator output signals on the basis of the second set of K decorrelator input signals; and
wherein the multi-channel decorrelator is configured to upmix the first set of K′ decorrelator output signals into a second set of N′ decorrelator output signals, wherein N′>K′;
wherein the multi-channel decorrelator is configured to premix the first set {circumflex over (Z)} of N decorrelator input signals into the second set {circumflex over (Z)}mix of K decorrelator input signals using a premixing matrix Mpre according to
{circumflex over (Z)}mix=Mpre{circumflex over (Z)}
wherein the multi-channel decorrelator is configured to obtain the first set {circumflex over (Z)}mixdec of K′ decorrelator output signals on the basis of the second set {circumflex over (Z)}mix of K decorrelator input signals, and
wherein the multi-channel decorrelator is configured to upmix the first set {circumflex over (Z)}mixdec of K′ decorrelator output signals into the second set W of N′ decorrelator output signals using a postmixing matrix Mpost according to
W=Mpost{circumflex over (Z)}mixdec;
wherein the multi-channel decorrelator is configured to obtain the postmixing matrix Mpost according to
Mpost=MpreH(MpreMpreH)−1.
Another embodiment may have a multi-channel decorrelator for providing a plurality of decorrelated signals on the basis of a plurality of decorrelator input signals,
wherein the multi-channel decorrelator is configured to premix a first set of N decorrelator input signals into a second set of K decorrelator input signals, wherein K<N;
wherein the multi-channel decorrelator is configured to provide a first set of K′ decorrelator output signals on the basis of the second set of K decorrelator input signals; and
wherein the multi-channel decorrelator is configured to upmix the first set of K′ decorrelator output signals into a second set of N′ decorrelator output signals, wherein N′>K′;
wherein the multi-channel decorrelator is configured to receive an information about a rendering configuration associated with the channel signals of the first set of N decorrelator input signals, and wherein the multi-channel decorrelator is configured to select a premixing matrix in dependence on the information about the rendering configuration.
Another embodiment may have a multi-channel decorrelator for providing a plurality of decorrelated signals on the basis of a plurality of decorrelator input signals,
wherein the multi-channel decorrelator is configured to premix a first set of N decorrelator input signals into a second set of K decorrelator input signals, wherein K<N;
wherein the multi-channel decorrelator is configured to provide a first set of K′ decorrelator output signals on the basis of the second set of K decorrelator input signals; and
wherein the multi-channel decorrelator is configured to upmix the first set of K′ decorrelator output signals into a second set of N′ decorrelator output signals, wherein N′>K′;
wherein the multi-channel decorrelator is configured to combine channel signals of the first set of N decorrelator input signals which are associated with spatially adjacent positions of an audio scene when performing the premixing.
Another embodiment may have a multi-channel decorrelator for providing a plurality of decorrelated signals on the basis of a plurality of decorrelator input signals,
wherein the multi-channel decorrelator is configured to premix a first set of N decorrelator input signals into a second set of K decorrelator input signals, wherein K<N;
wherein the multi-channel decorrelator is configured to provide a first set of K′ decorrelator output signals on the basis of the second set of K decorrelator input signals; and
wherein the multi-channel decorrelator is configured to upmix the first set of K′ decorrelator output signals into a second set of N′ decorrelator output signals, wherein N′>K′;
wherein the multi-channel decorrelator is configured to combine channel signals of the first set of N decorrelator input signals which are associated with a horizontal pair of spatial positions having a left side position and a right side position.
Another embodiment may have a multi-channel decorrelator for providing a plurality of decorrelated signals on the basis of a plurality of decorrelator input signals,
wherein the multi-channel decorrelator is configured to premix a first set of N decorrelator input signals into a second set of K decorrelator input signals, wherein K<N;
wherein the multi-channel decorrelator is configured to provide a first set of K′ decorrelator output signals on the basis of the second set of K decorrelator input signals; and
wherein the multi-channel decorrelator is configured to upmix the first set of K′ decorrelator output signals into a second set of N′ decorrelator output signals, wherein N′>K′;
wherein the multi-channel decorrelator is configured to combine at least four channel signals of the first set of N decorrelator input signals, wherein at least two of said at least four channel signals are associated with spatial positions on a left side of an audio scene, and wherein at least two of said at least four channel signals are associated with spatial positions on a right side of the audio scene.
Another embodiment may have a multi-channel decorrelator for providing a plurality of decorrelated signals on the basis of a plurality of decorrelator input signals,
wherein the multi-channel decorrelator is configured to premix a first set of N decorrelator input signals into a second set of K decorrelator input signals, wherein K<N;
wherein the multi-channel decorrelator is configured to provide a first set of K′ decorrelator output signals on the basis of the second set of K decorrelator input signals; and
wherein the multi-channel decorrelator is configured to upmix the first set of K′ decorrelator output signals into a second set of N′ decorrelator output signals, wherein N′>K′;
wherein the multi-channel decorrelator is configured to receive a complexity information describing a number K of decorrelator input signals of the second set of decorrelator input signals, and wherein the multi-channel decorrelator is configured to select a premixing matrix in dependence on the complexity information.
Still another embodiment may have a multi-channel audio decoder for providing at least two output audio signals on the basis of an encoded representation,
wherein the multi-channel audio decoder has a multi-channel decorrelator for providing a plurality of decorrelated signals on the basis of a plurality of decorrelator input signals,
wherein the multi-channel decorrelator is configured to premix a first set of N decorrelator input signals into a second set of K decorrelator input signals, wherein K<N;
wherein the multi-channel decorrelator is configured to provide a first set of K′ decorrelator output signals on the basis of the second set of K decorrelator input signals; and
wherein the multi-channel decorrelator is configured to upmix the first set of K′ decorrelator output signals into a second set of N′ decorrelator output signals, wherein N′>K′;
wherein the multi-channel audio decoder is configured to select a premixing matrix for usage by the multi-channel decorrelator in dependence on an output configuration describing an allocation of the output audio signals with spatial positions of an audio scene.
Another embodiment may have a multi-channel audio decoder for providing at least two output audio signals on the basis of an encoded representation,
wherein the multi-channel audio decoder has a multi-channel decorrelator for providing a plurality of decorrelated signals on the basis of a plurality of decorrelator input signals,
wherein the multi-channel decorrelator is configured to premix a first set of N decorrelator input signals into a second set of K decorrelator input signals, wherein K<N;
wherein the multi-channel decorrelator is configured to provide a first set of K′ decorrelator output signals on the basis of the second set of K decorrelator input signals; and
wherein the multi-channel decorrelator is configured to upmix the first set of K′ decorrelator output signals into a second set of N′ decorrelator output signals, wherein N′>K′;
wherein the multi-channel audio decoder is configured to select between three or more different premixing matrices for usage by the multi-channel decorrelator in dependence on a control information included in the encoded representation for a given output configuration, wherein each of the three or more different premixing matrices is associated with a different number of signals of the second set of K decorrelator input signals.
Another embodiment may have a multi-channel audio decoder for providing at least two output audio signals on the basis of an encoded representation,
wherein the multi-channel audio decoder has a multi-channel decorrelator for providing a plurality of decorrelated signals on the basis of a plurality of decorrelator input signals,
wherein the multi-channel decorrelator is configured to premix a first set of N decorrelator input signals into a second set of K decorrelator input signals, wherein K<N;
wherein the multi-channel decorrelator is configured to provide a first set of K′ decorrelator output signals on the basis of the second set of K decorrelator input signals; and
wherein the multi-channel decorrelator is configured to upmix the first set of K′ decorrelator output signals into a second set of N′ decorrelator output signals, wherein N′>K′;
wherein the multi-channel audio decoder is configured to select a premixing matrix for usage by the multi-channel decorrelator in dependence on a mixing matrix which is used by an format converter or renderer which receives the at least two output audio signals.
According to another embodiment, a method for providing a plurality of decorrelated signals on the basis of a plurality of decorrelator input signals may have the steps of:
premixing a first set of N decorrelator input signals into a second set of K decorrelator input signals, wherein K<N;
providing a first set of K′ decorrelator output signals on the basis of the second set of K decorrelator input signals; and
upmixing the first set of K′ decorrelator output signals into a second set of N′ decorrelator output signals, wherein N′>K′;
wherein the first set {circumflex over (Z)} of N decorrelator input signals is premixed into the second set {circumflex over (Z)}mix of K decorrelator input signals using a premixing matrix Mpre according to
{circumflex over (Z)}mix=Mpre{circumflex over (Z)}
wherein the first set {circumflex over (Z)}mixdec of K′ decorrelator output signals is obtained on the basis of the second set {circumflex over (Z)}mix of K decorrelator input signals, and
wherein the first set {circumflex over (Z)}mixdec of K′ decorrelator output signals is upmixed into the second set W of N′ decorrelator output signals using a postmixing matrix Mpost according to
W=Mpost{circumflex over (Z)}mixdec;
wherein the premixing matrix Mpre is selected in dependence on correlation characteristics or covariance characteristics of the channel signals of the first set {circumflex over (Z)} of N decorrelator input signals.
According to another embodiment, a method for providing a plurality of decorrelated signals on the basis of a plurality of decorrelator input signals may have the steps of:
premixing a first set of N decorrelator input signals into a second set of K decorrelator input signals, wherein K<N;
providing a first set of K′ decorrelator output signals on the basis of the second set of K decorrelator input signals; and
upmixing the first set of K′ decorrelator output signals into a second set of N′ decorrelator output signals, wherein N′>K′;
wherein he first set {circumflex over (Z)} of N decorrelator input signals is premixed into the second set {circumflex over (Z)}mix of K decorrelator input signals using a premixing matrix Mpre according to
{circumflex over (Z)}mix=Mpre{circumflex over (Z)}
wherein the first set {circumflex over (Z)}mixdec of K′ decorrelator output signals is obtained on the basis of the second set {circumflex over (Z)}mix of K decorrelator input signals, and
wherein the first set {circumflex over (Z)}mixdec of K′ decorrelator output signals is upmixed into the second set W of N′ decorrelator output signals using a postmixing matrix Mpost according to
W=Mpost{circumflex over (Z)}mixdec;
wherein the postmixing matrix Mpost is obtained according to
Mpost=MpreH(MpreMpreH)−1.
According to another embodiment, a method for providing a plurality of decorrelated signals on the basis of a plurality of decorrelator input signals may have the steps of:
premixing a first set of N decorrelator input signals into a second set of K decorrelator input signals, wherein K<N;
providing a first set of K′ decorrelator output signals on the basis of the second set of K decorrelator input signals; and
upmixing the first set of K′ decorrelator output signals into a second set of N′ decorrelator output signals, wherein N′>K′;
wherein the method has receiving an information about a rendering configuration associated with the channel signals of the first set of N decorrelator input signals, and wherein a premixing matrix is selected in dependence on the information about the rendering configuration.
According to another embodiment, a method for providing a plurality of decorrelated signals on the basis of a plurality of decorrelator input signals may have the steps of:
premixing a first set of N decorrelator input signals into a second set of K decorrelator input signals, wherein K<N;
providing a first set of K′ decorrelator output signals on the basis of the second set of K decorrelator input signals; and
upmixing the first set of K′ decorrelator output signals into a second set of N′ decorrelator output signals, wherein N′>K′;
wherein channel signals of the first set of N decorrelator input signals which are associated with spatially adjacent positions of an audio scene are combined when performing the premixing.
According to still another embodiment, a method for providing a plurality of decorrelated signals on the basis of a plurality of decorrelator input signals may have the steps of:
premixing a first set of N decorrelator input signals into a second set of K decorrelator input signals, wherein K<N;
providing a first set of K′ decorrelator output signals on the basis of the second set of K decorrelator input signals; and
upmixing the first set of K′ decorrelator output signals into a second set of N′ decorrelator output signals, wherein N′>K′;
wherein channel signals of the first set of N decorrelator input signals which are associated with a horizontal pair of spatial positions having a left side position and a right side position are combined.
According to another embodiment, a method for providing a plurality of decorrelated signals on the basis of a plurality of decorrelator input signals may have the steps of:
premixing a first set of N decorrelator input signals into a second set of K decorrelator input signals, wherein K<N;
providing a first set of K′ decorrelator output signals on the basis of the second set of K decorrelator input signals; and
upmixing the first set of K′ decorrelator output signals into a second set of N′ decorrelator output signals, wherein N′>K′;
wherein at least four channel signals of the first set of N decorrelator input signals are combined, wherein at least two of said at least four channel signals are associated with spatial positions on a left side of an audio scene, and wherein at least two of said at least four channel signals are associated with spatial positions on a right side of the audio scene.
According to another embodiment, a method for providing a plurality of decorrelated signals on the basis of a plurality of decorrelator input signals may have the steps of:
premixing a first set of N decorrelator input signals into a second set of K decorrelator input signals, wherein K<N;
providing a first set of K′ decorrelator output signals on the basis of the second set of K decorrelator input signals; and
upmixing the first set of K′ decorrelator output signals into a second set of N′ decorrelator output signals, wherein N′>K′;
wherein the method has receiving a complexity information describing a number K of decorrelator input signals of the second set of decorrelator input signals, and wherein a premixing matrix is selected in dependence on the complexity information.
Another embodiment may have a method for providing at least two output audio signals on the basis of an encoded representation,
wherein the method has providing a plurality of decorrelated signals on the basis of a plurality of decorrelator input signals,
wherein providing a plurality of decorrelated signals on the basis of a plurality of decorrelator input signals has:
premixing a first set of N decorrelator input signals into a second set of K decorrelator input signals, wherein K<N;
providing a first set of K′ decorrelator output signals on the basis of the second set of K decorrelator input signals; and
upmixing the first set of K′ decorrelator output signals into a second set of N′ decorrelator output signals, wherein N′>K′;
wherein a premixing matrix for usage by the multi-channel decorrelator is selected in dependence on an output configuration describing an allocation of the output audio signals with spatial positions of an audio scene.
Another embodiment may have a method for providing at least two output audio signals on the basis of an encoded representation,
wherein the method has providing a plurality of decorrelated signals on the basis of a plurality of decorrelator input signals,
wherein providing a plurality of decorrelated signals on the basis of a plurality of decorrelator input signals has:
premixing a first set of N decorrelator input signals into a second set of K decorrelator input signals, wherein K<N;
providing a first set of K′ decorrelator output signals on the basis of the second set of K decorrelator input signals; and
upmixing the first set of K′ decorrelator output signals into a second set of N′ decorrelator output signals, wherein N′>K′;
wherein the method has selecting between three or more different premixing matrices for usage by the multi-channel decorrelator in dependence on a control information included in the encoded representation for a given output configuration, wherein each of the three or more different premixing matrices is associated with a different number of signals of the second set of K decorrelator input signals
Another embodiment may have a method for providing at least two output audio signals on the basis of an encoded representation,
wherein the method has providing a plurality of decorrelated signals on the basis of a plurality of decorrelator input signals,
wherein providing a plurality of decorrelated signals on the basis of a plurality of decorrelator input signals has:
premixing a first set of N decorrelator input signals into a second set of K decorrelator input signals, wherein K<N;
providing a first set of K′ decorrelator output signals on the basis of the second set of K decorrelator input signals; and
upmixing the first set of K′ decorrelator output signals into a second set of N′ decorrelator output signals, wherein N′>K′;
wherein a premixing matrix for usage by the multi-channel decorrelator is selected in dependence on a mixing matrix which is used by an format converter or renderer which receives the at least two output audio signals.
Another embodiment may have a computer program for performing the above methods when the computer program runs on a computer.
An embodiment according to the invention creates a multi-channel decorrelator for providing a plurality of decorrelated signals on the basis of a plurality of decorrelator input signals. The multi-channel decorrelator is configured to premix a first set of N decorrelator input signals into a second set of K decorrelator input signals, wherein K<N. The multi-channel decorrelator is configured to provide a first set of K′ decorrelator output signals on the basis of the second set of K decorrelator input signals. The multi-channel decorrelator is further configured to upmix the first set of K′ decorrelator output signals into a second set of N′ decorrelator output signals, wherein N′>K′.
This embodiment according to the invention is based on the idea that a complexity of the decorrelation can be reduced by premixing the first set of N decorrelator input signals into a second set of K decorrelator input signals, wherein the second set of K decorrelator input signals comprises less signals than the first set of N decorrelator input signals. Accordingly, the fundamental decorrelator functionality is performed on only K signals (the K decorrelator input signals of the second set) such that, for example, only K (individual) decorrelators (or individual decorrelations) are necessitated (and not N decorrelators). Moreover, to provide N′ decorrelator output signals, an upmix is performed, wherein the first set of K′ decorrelator output signals is upmixed into the second set of N′ decorrelator output signals. Accordingly, it is possible to obtain a comparatively large number of decorrelated signals (namely, N′ signals of the second set of decorrelator output signals) on the basis of a comparatively large number of decorrelator input signals (namely, N signals of the first set of decorrelator input signals), wherein a core decorrelation functionality is performed on the basis of only K signals (for example using only K individual decorrelators). Thus, a significant gain in decorrelation efficiency is achieved, which helps to save processing power and resources (for example, energy).
In one embodiment, the number K of signals of the second set of decorrelator input signals is equal to the number K′ of signals of the first set of decorrelator output signals. Accordingly, there may for example be K individual decorrelators, each of which receives one decorrelator input signal (of the second set of decorrelator input signals) from the premixing, and each of which provides one decorrelator output signals (of the first set of decorrelator output signals) to the upmixing. Thus, simple individual decorrelators can be used, each of which provides one output signal on the basis of one input signal.
In another embodiment, number N of signals of the first set of decorrelator input signals may be equal to the number N′ of signals of the second set of decorrelator output signals. Thus, the number of signals received by the multi-channel decorrelator is equal to the number of signals provided by the multi-channel decorrelator, such that the multi-channel decorrelator appears, from outside, like a bank of N independent decorrelators (wherein, however, the decorrelation result may comprise some imperfections due to the usage of only K input signals for the core decorrelator). Accordingly, the multi-channel decorrelator may be used as drop-in replacement for conventional decorrelators having an equal number of input signals and output signals. Moreover, it should be noted that the upmixing may, for example, be derived from the premixing in such a configuration with moderate effort.
In one embodiment, the number N of signals of the first set of decorrelator input signals may be larger than or equal to 3, and the number N′ of signals of the second set of decorrelator output signals may also be larger than or equal to 3. In such a case, the multi-channel decorrelator may provide particular efficiency.
In one embodiment, the multi-channel decorrelator may be configured to premix the first set of N decorrelator input signals into a second set of K decorrelator input signals using a premixing matrix (i.e., using a linear premixing functionality). In this case, the multi-channel decorrelator may be configured to obtain the first set of K′ decorrelator output signals on the basis of the second set of K decorrelator input signals (for example, using individual decorrelators). The multi-channel decorrelator may also be configured to upmix the first set of K′ decorrelator output signals into the second set of N′ decorrelator output signals using a postmixing matrix, i.e., using a linear postmixing function. Accordingly, distortions may be kept small. Also, the premixing and post mixing (also designated as upmixing) may be performed in a computationally efficient manner.
In one embodiment, the multi-channel decorrelator may be configured to select the premixing matrix in dependence on spatial positions to which the channel signals of the first set of N decorrelator input signals are associated. Accordingly, spatial dependencies (or correlations) may be considered in the premixing process, which is helpful to avoid an excessive degradation due to the premixing process performed in the multi-channel decorrelator.
In one embodiment, the multi-channel decorrelator may be configured to select the premixing matrix in dependence on correlation characteristics or covariance characteristics of the channel signals of the first set of N decorrelator input signals. Such a functionality may also help to avoid excessive distortions due to the premixing performed by the multi-channel decorrelator. For example, decorrelator input signals (of the first set of decorrelator input signals), which are closely related (i.e., comprise a high cross-correlation or a high cross-covariance) may, for example, be combined into a single decorrelator input signal of the second set of decorrelator input signals, and may consequently be processed, for example, by a common individual decorrelator (of the decorrelator core). Thus, it can be avoided that substantially different decorrelator input signals (of the first set of decorrelator input signals) are premixed (or downmixed) into a single decorrelator input signal (of the second set of decorrelator input signals), which is input into the decorrelator core, since this will typically result in inappropriate decorrelator output signals (which would, for example, disturb a spatial perception when used to bring audio signals to desired cross-correlation characteristics or cross-covariance characteristics). Accordingly, the multi-channel decorrelator may decide, in an intelligent manner, which signals should be combined in the premixing (or downmixing) process to allow for a good compromise between decorrelation efficiency and audio quality.
In one embodiment, the multi-channel decorrelator is configured to determine the premixing matrix such that a matrix-product between the premixing matrix and a Hermitian thereof is well-conditioned with respect to an inversion operation. Accordingly, the premixing matrix can be chosen such that a postmixing matrix can be determined without numerical problems.
In one embodiment, the multi-channel decorrelator is configured to obtain the postmixing matrix on the basis of the premixing matrix using some matrix multiplication and matrix inversion operations. In this way, the postmixing matrix can be obtained efficiently, such that the postmixing matrix is well-adapted to the premixing process.
In one embodiment, the multi-channel decorrelator is configured to receive an information about a rendering configuration associated with the channel signals of the first set of N decorrelator input signals. In this case, the multi-channel decorrelator is configured to select a premixing matrix in dependence on the information about the rendering configuration. Accordingly, the premixing matrix may be selected in a manner which is well-adapted to the rendering configuration, such that a good audio quality can be obtained.
In one embodiment, the multi-channel decorrelator is configured to combine channel signals of the first set of N decorrelator input signals which are associated with spatially adjacent positions of an audio scene when performing the premixing. Thus, the fact that channel signals associated with spatially adjacent positions of an audio scene are typically similar is exploited when setting up the premixing. Consequently, similar audio signals may be combined in the premixing and processed using the same individual decorrelator in the decorrelator core. Accordingly, inacceptable degradations of the audio content can be avoided.
In one embodiment, the multi-channel decorrelator is configured to combine channel signals of the first set of N decorrelator input signals which are associated with vertically spatially adjacent positions of an audio scene when performing the premixing. This concept is based on the finding that audio signals from vertically spatially adjacent positions of the audio scene are typically similar. Moreover, the human perception is not particularly sensitive with respect to differences between signals associated with vertically spatially adjacent positions of the audio scene. Accordingly, it has been found that combining audio signals associated with vertically spatially adjacent positions of the audio scene does not result in a substantial degradation of a hearing impression obtained on the basis of the decorrelated audio signals.
In one embodiment, the multi-channel decorrelator may be configured to combine channel signals of the first set of N decorrelator input signals which are associated with a horizontal pair of spatial positions comprising a left side position and a right side position. It has been found that channel signals which are associated with a horizontal pair of spatial positions comprising a left side position and a right side position are typically also somewhat related since channel signals associated with a horizontal pair of spatial positions are typically used to obtain a spatial impression. Accordingly, it has been found that it is a reasonable solution to combine channel signals associated with a horizontal pair of spatial positions, for example if it is not sufficient to combine channel signals associated with vertically spatially adjacent positions of the audio scene, because combining channel signals associated with a horizontal pair of spatial positions typically does not result in an excessive degradation of a hearing impression.
In one embodiment, the multi-channel decorrelator is configured to combine at least four channel signals of the first set of N decorrelator input signals, wherein at least two of said at least four channel signals are associated with spatial positions on a left side of an audio scene, and wherein at least two of said at least four channel signals are associated with spatial positions on a right side of an audio scene. Accordingly, four or more channels signals are combined, such that an efficient decorrelation can be obtained without significantly comprising a hearing impression.
In one embodiment, the at least two left-sided channel signals (i.e., channel signals associated with spatial positions on the left side of the audio scene) to be combined are associated with spatial positions which are symmetrical, with respect to a center plane of the audio scene, to the spatial positions associated with the at least two right-sided channel signals to be combined (i.e., channel signals associated with spatial positions on the right side of the audio scene). It has been found that a combination of channel signals associated with “symmetrical” spatial positions typically brings along good results, since signals associated with such “symmetrical” spatial positions are typically somewhat related, which is advantageous for performing the common (combined) decorrelation.
In one embodiment, the multi-channel decorrelator is configured to receive a complexity information describing a number K of decorrelator input signals of the second set of decorrelator input signals. In this case, the multi-channel decorrelator may be configured to select a premixing matrix in dependence on the complexity information. Accordingly, the multi-channel decorrelator can be adapted flexibly to different complexity requirements. Thus, it is possible to vary a compromise between audio quality and complexity.
In one embodiment, the multi-channel decorrelator is configured to gradually (for example, step-wisely) increase a number of decorrelator input signals of the first set of decorrelator input signals which are combined together to obtain the decorrelator input signals of the second set of decorrelator input signals with a decreasing value of the complexity information. Accordingly, it is possible to combine more and more decorrelator input signals of the first set of decorrelator input signals (for example, into a single decorrelator input signal of the second set of decorrelator input signals) if it is desired to decrease the complexity, which allows to vary the complexity with little effort.
In one embodiment, the multi-channel decorrelator is configured to combine only channel signals of the first set of N decorrelator input signals which are associated with vertically spatially adjacent positions of an audio scene when performing the premixing for a first value of the complexity information. However, the multi-channel decorrelator may (also) be configured to combine at least two channel signals of the first set of N decorrelator input signals which are associated with vertically spatially adjacent positions on the left side of the audio scene and at least two channel signals of the first set of N decorrelator input signals which are associated with vertically spatially adjacent positions on the right side of the audio scene in order to obtain a given signal of the second set of decorrelator input signals when performing the premixing for a second value of the complexity information. In other words, for the first value of the complexity information, no combination of channel signals from different sides of the audio scene may be performed, which results in a particularly good quality of the audio signals (and of a hearing impression, which can be obtained on the basis of the decorrelated audio signals). In contrast, if a smaller complexity is necessitated, a horizontal combination may also be performed in addition to the vertical combination. It has been found that this a reasonable concept for a step-wise adjustment of the complexity, wherein a somewhat higher degradation of a hearing impression is found for reduced complexity.
In one embodiment, the multi-channel decorrelator is configured to combine at least four channel signals of the first set of N decorrelator input signals, wherein at least two of said at least four channel signals are associated with spatial positions on a left side of an audio scene, and wherein at least two of said at least four channel signals are associated with spatial positions on a right side of the audio scene when performing the premixing for a second value of the complexity information. This concept is based on the finding that a comparatively low computational complexity can be obtained by combining at least two channel signals associated with spatial positions on a left side of the audio scene and at least two channel signals associated with spatial positions on a right side of the audio scene, even if said channel signals are not vertically adjacent (or at least not perfectly vertically adjacent).
In one embodiment, the multi-channel decorrelator is configured to combine at least two channel signals of the first set of N decorrelator input signals which are associated with vertically spatially adjacent positions on a left side of the audio scene, in order to obtain a first decorrelator input signal of the second set of decorrelator input signals, and to combine at least two channel signals of the first set of N decorrelator input signals which are associated with vertically spatially adjacent positions on a right side of the audio scene, in order to obtain a second decorrelator input signal of the second set of decorrelator input signals for a first value of the complexity information. Moreover, the multi-channel decorrelator may be configured to combine the at least two channel signals of the first set of N decorrelator input signals which are associated with vertically spatially adjacent positions on the left side of the audio scene and the at least two channel signals of the first set of N decorrelator input signals which are associated with vertically spatially adjacent positions on the right side of the audio scene, in order to obtain a decorrelator input signal of the second set of decorrelator input signals for a second value of the complexity information. In this case, a number of decorrelator input signals of the second set of decorrelator input signals is larger for the first value of the complexity information than for the second value of the complexity information. In other words, four channel signals, which are used to obtain two decorrelator input signals of the second set of decorrelator input signals for the first value of the complexity information may be used to obtain a single decorrelator input signal of the second set of decorrelator input signals for the second value of the complexity information. Thus, signals which serve as input signals for two individual decorrelators for the first value of the complexity information are combined to serve as input signals for a single individual decorrelator for the second value of the complexity information. Thus, an efficient reduction of the number of individual decorrelators (or of the number of decorrelator input signals of the second set of decorrelator input signals) can be obtained for a reduced value of the complexity information.
An embodiment according to the invention creates a multi-channel audio decoder for providing at least two output audio signals on the basis of an encoded representation. The multi-channel audio decoder comprises a multi-channel decorrelator, as discussed herein.
This embodiment is based on the finding that the multi-channel audio decorrelator is well-suited for application in a multi-channel audio decoder.
In one embodiment, the multi-channel audio decoder is configured to render a plurality of decoded audio signals, which are obtained on the basis of the encoded representation, in dependence on one or more rendering parameters, to obtain a plurality of rendered audio signals. The multi-channel audio decoder is configured to derive one or more decorrelated audio signals from the rendered audio signals using the multi-channel decorrelator, wherein the rendered audio signals constitute the first set of decorrelator input signals, and wherein the second set of decorrelator output signals constitute the decorrelated audio signals. The multi-channel audio decoder is configured to combine the rendered audio signals, or a scaled version thereof, with the one or more decorrelated audio signals (of the second set of decorrelator output signals), to obtain the output audio signals. This embodiment according to the invention is based on the finding that the multi-channel decorrelator described herein is well-suited for a post-rendering processing, wherein a comparatively large number of rendered audio signals is input into the multi-channel decorrelator, and wherein a comparatively large number of decorrelated signals is then combined with the rendered audio signals. Moreover, it has been found that the imperfections caused by the usage of a comparatively small number of individual decorrelators (complexity reduction in the multi-channel decorrelator) typically does not result in a severe degradation of a quality of the output audio signals output by the multi-channel decoder.
In one embodiment, the multi-channel audio decoder is configured to select a premixing matrix for usage by the multi-channel decorrelator in dependence on a control information included in the encoded representation. Accordingly, it is even possible for an audio encoder to control the quality of the decorrelation, such that the quality of the decorrelation can be well-adapted to the specific audio content, which brings along a good tradeoff between audio quality and decorrelation complexity.
In one embodiment, the multi-channel audio decoder is configured to select a premixing matrix for usage by the multi-channel decorrelator in dependence on an output configuration describing an allocation of output audio signals with spatial positions of the audio scene. Accordingly, the multi-channel decorrelator can be adapted to the specific rendering scenario, which helps to avoid substantial degradation of the audio quality by the efficient decorrelation.
In one embodiment, the multi-channel audio decoder is configured to select between three or more different premixing matrices for usage by the multi-channel decorrelator in dependence on a control information included in the encoded representation for a given output representation. In this case, each of the three or more different premixing matrices is associated with a different number of signals of the second set of K decorrelator input signals. Thus, the complexity of the decorrelation can be adjusted over a wide range.
In one embodiment, the multi-channel audio decoder is configured to select a premixing matrix (Mpre) for usage by the multi-channel decorrelator in dependence on a mixing matrix (Dconv, Drender) which is used by an format converter or renderer which receives the at least two output audio signals.
In another embodiment, the multi-channel audio decoder is configured to select the premixing matrix (Mpre) for usage by the multi-channel decorrelator to be equal to a mixing matrix (Dconv, Drender) which is used by a format converter or renderer which receives the at least two output audio signals.
An embodiment according to the invention creates a multi-channel audio encoder for providing an encoded representation on the basis of at least two input audio signals. The multi-channel audio encoder is configured to provide one or more downmix signals on the basis of the at least two input audio signals. The multi-channel audio encoder is also configured to provide one or more parameters describing a relationship between the at least two input audio signals. Moreover, the multi-channel audio encoder is configured to provide a decorrelation complexity parameter describing a complexity of a decorrelation to be used at the side of an audio decoder. Accordingly, the multi-channel audio encoder is able to control the multi-channel audio decoder described above, such that the complexity of the decorrelation can be adjusted to the requirements of the audio content which is encoded by the multi-channel audio encoder.
Another embodiment according to the invention creates a method for providing a plurality of decorrelated signals on the basis of a plurality of decorrelator input signals. The method comprises premixing a first set of N decorrelator input signals into a second set of K decorrelator input signals, wherein K<N. The method also comprises providing a first set of K′ decorrelator output signals on the basis of the second set of K decorrelator input signals. Moreover, the method comprises upmixing the first set of K′ decorrelator output signals into a second set of N′ decorrelator output signals, wherein N′>K′. This method is based on the same ideas as the above described multi-channel decorrelator.
Another embodiment according to the invention creates a method for providing at least two output audio signals on the basis of an encoded representation. The method comprises providing a plurality of decorrelated signals on the basis of a plurality of decorrelator input signals, as described above. This method is based on the same findings as the multi-channel audio decoder mentioned above.
Another embodiment creates a method for providing an encoded representation on the basis of at least two input audio signals. The method comprises providing one or more downmix signals on the basis of the at least two input audio signals. The method also comprises providing one or more parameters describing a relationship between the at least two input audio signals. Further, the method comprises providing a decorrelation complexity parameter describing a complexity of a decorrelation to be used at the side of an audio decoder. This method is based on the same ideas as the above described audio encoder.
Furthermore, embodiments according to the invention create a computer program for performing said methods.
Another embodiment according to the invention creates an encoded audio representation. The encoded audio representation comprises an encoded representation of a downmix signal and an encoded representation of one or more parameters describing a relationship between the at least two input audio signals. Furthermore, the encoded audio representation comprises an encoded decorrelation method parameter describing which decorrelation mode out of a plurality of decorrelation modes should be used at the side of an audio decoder. Accordingly, the encoded audio representation allows to control the multi-channel decorrelator described above, as well as the multi-channel audio decoder described above.
Moreover, it should be noted that the methods described above can be supplemented by any of the features and functionality described with respect to the apparatuses as mentioned above.
Embodiments according to the present invention will subsequently be described taking reference to the enclosed figures in which:
The multi-channel audio decoder 100 is configured to receive an encoded representation 110 and to provide, on the basis thereof, at least two output audio signals 112, 114.
The multi-channel audio decoder 100 may comprise a decoder 120 which is configured to provide decoded audio signals 122 on the basis of the encoded representation 110. Moreover, the multi-channel audio decoder 100 comprises a renderer 130, which is configured to render a plurality of decoded audio signals 122, which are obtained on the basis of the encoded representation 110 (for example, by the decoder 120) in dependence on one or more rendering parameters 132, to obtain a plurality of rendered audio signals 134, 136. Moreover, the multi-channel audio decoder 100 comprises a decorrelator 140, which is configured to derive one or more decorrelated audio signals 142, 144 from the rendered audio signals 134, 136. Moreover, the multi-channel audio decoder 100 comprises a combiner 150, which is configured to combine the rendered audio signals 134, 136, or a scaled version thereof, with the one or more decorrelated audio signals 142, 144 to obtain the output audio signals 112, 114.
However, it should be noted that a different hardware structure of the multi-channel audio decoder 100 may be possible, as long as the functionalities described above are given.
Regarding the functionality of the multi-channel audio decoder 100, it should be noted that the decorrelated audio signals 142, 144 are derived from the rendered audio signals 134, 136, and that the decorrelated audio signals 142, 144 are combined with the rendered audio signals 134, 136 to obtain the output audio signals 112, 114. By deriving the decorrelated audio signals 142, 144 from the rendered audio signals 134, 136, a particularly efficient processing can be achieved, since the number of rendered audio signals 134, 136 is typically independent from the number of decoded audio signals 122 which are input into the renderer 130. Thus, the decorrelation effort is typically independent from the number of decoded audio signals 122, which improves the implementation efficiency. Moreover, applying the decorrelation after the rendering avoids the introduction of artifacts, which could be caused by the renderer when combining multiple decorrelated signals in the case that the decorrelation is applied before the rendering. Moreover, characteristics of the rendered audio signals can be considered in the decorrelation performed by the decorrelator 140, which typically results in output audio signals of good quality.
Moreover, it should be noted that the multi-channel audio decoder 100 can be supplemented by any of the features and functionalities described herein. In particular, it should be noted that individual improvements as described herein may be introduced into the multi-channel audio decoder 100 in order to thereby even improve the efficiency of the processing and/or the quality of the output audio signals.
Moreover, the multi-channel audio encoder 200 also comprises a decorrelation method parameter provider 240, which is configured to provide a decorrelation method parameter 242 describing which decorrelation mode out of a plurality of decorrelation modes should be used at the side of an audio decoder. The one or more downmix signals 222, the one or more parameters 232 and the decorrelation method parameter 242 are included, for example, in an encoded form, into the encoded representation 214.
However, it should be noted that the hardware structure of the multi-channel audio encoder 200 may be different, as long as the functionalities as described above are fulfilled. In other words, the distribution of the functionalities of the multi-channel audio encoder 200 to individual blocks (for example, to the downmix signal provider 220, to the parameter provider 230 and to the decorrelation method parameter provider 240) should only be considered as an example.
Regarding the functionality of the multi-channel audio encoder 200, it should be noted that the one or more downmix signals 222 and the one or more parameters 232 are provided in a conventional way, for example like in an SAOC multi-channel audio encoder or in a USAC multi-channel audio encoder. However, the decorrelation method parameter 242, which is also provided by the multi-channel audio encoder 200 and included into the encoded representation 214, can be used to adapt a decorrelation mode to the input audio signals 210, 212 or to a desired playback quality. Accordingly, the decorrelation mode can be adapted to different types of audio content. For example, different decorrelation modes can be chosen for types of audio contents in which the input audio signals 210, 212 are strongly correlated and for types of audio content in which the input audio signals 210, 212 are independent. Moreover, different decorrelation modes can, for example, be signaled by the decorrelation mode parameter 242 for types of audio contents in which a spatial perception is particularly important and for types of audio content in which a spatial impression is less important or even of subordinate importance (for example, when compared to a reproduction of individual channels). Accordingly, a multi-channel audio decoder, which receives the encoded representation 214, can be controlled by the multi-channel audio encoder 200, and may be set to a decoding mode which brings along a best possible compromise between decoding complexity and reproduction quality.
Moreover, it should be noted that the multi-channel audio encoder 200 may be supplemented by any of the features and functionalities described herein. It should be noted that the possible additional features and improvements described herein may be added to the multi-channel audio encoder 200 individually or in combination, to thereby improve (or enhance) the multi-channel audio encoder 200.
It should be noted that the method 300 is based on the same considerations as the multi-channel audio decoder 100 according to
It should be noted that the method 400 is based on the same considerations as the multi-channel audio encoder 200 according to
Moreover, it should be noted that the order of the steps 410, 420, 430 can be varied flexibly, and that the steps 410, 420, 430 may also be performed in parallel as far as this is possible in an execution environment for the method 400. Moreover, it should be noted that the method 400 can be supplemented by any of the features and functionalities described herein, either individually or in combination. For example, the method 400 may be supplemented by any of the features and functionalities described herein with respect to the multi-channel audio encoders. However, it is also possible to introduce features and functionalities which correspond to the features and functionalities of the multi-channel audio decoders described herein, which receive the encoded representation 432.
The encoded audio representation 500 comprises an encoded representation 510 of a downmix signal, an encoded representation 520 of one or more parameters describing a relationship between at least two audio signals. Moreover, the encoded audio representation 500 also comprises an encoded decorrelation method parameter 530 describing which decorrelation mode out of a plurality of decorrelation modes should be used at the side of an audio decoder. Accordingly, the encoded audio representation allows to signal a decorrelation mode from an audio encoder to an audio decoder. Accordingly, it is possible to obtain a decorrelation mode which is well-adapted to the characteristics of the audio content (which is described, for example, by the encoded representation 510 of one or more downmix signals and by the encoded representation 520 of one or more parameters describing a relationship between at least two audio signals (for example, the at least two audio signals which have been downmixed into the encoded representation 510 of one or more downmix signals)). Thus, the encoded audio representation 500 allows for a rendering of an audio content represented by the encoded audio representation 500 with a particularly good auditory spatial impression and/or a particularly good tradeoff between auditory spatial impression and decoding complexity.
Moreover, it should be noted that the encoded representation 500 may be supplemented by any of the features and functionalities described with respect to the multi-channel audio encoders and the multi-channel audio decoders, either individually or in combination.
The multi-channel decorrelator 600 is configured to receive a first set of N decorrelator input signals 610a to 610n and provide, on the basis thereof, a second set of N′ decorrelator output signals 612a to 612n′. In other words, the multi-channel decorrelator 600 is configured for providing a plurality of (at least approximately) decorrelated signals 612a to 612n′ on the basis of the decorrelator input signals 610a to 610n.
The multi-channel decorrelator 600 comprises a premixer 620, which is configured to premix the first set of N decorrelator input signals 610a to 610n into a second set of K decorrelator input signals 622a to 622k, wherein K is smaller than N (with K and N being integers). The multi-channel decorrelator 600 also comprises a decorrelation (or decorrelator core) 630, which is configured to provide a first set of K′ decorrelator output signals 632a to 632k′ on the basis of the second set of K decorrelator input signals 622a to 622k. Moreover, the multi-channel decorrelator comprises an postmixer 640, which is configured to upmix the first set of K′ decorrelator output signals 632a to 632k′ into a second set of N′ decorrelator output signals 612a to 612n′, wherein N′ is larger than K′ (with N′ and K′ being integers).
However, it should be noted that the given structure of the multi-channel decorrelator 600 should be considered as an example only, and that it is not necessary to subdivide the multi-channel decorrelator 600 into functional blocks (for example, into the premixer 620, the decorrelation or decorrelator core 630 and the postmixer 640) as long as the functionality described herein is provided.
Regarding the functionality of the multi-channel decorrelator 600, it should also be noted that the concept of performing a premixing, to derive the second set of K decorrelator input signals from the first set of N decorrelator input signals, and of performing the decorrelation on the basis of the (premixed or “downmixed”) second set of K decorrelator input signals brings along a reduction of a complexity when compared to a concept in which the actual decorrelation is applied, for example, directly to N decorrelator input signals. Moreover, the second (upmixed) set of N′ decorrelator output signals is obtained on the basis of the first (original) set of decorrelator output signals, which are the result of the actual decorrelation, on the basis of an postmixing, which may be performed by the upmixer 640. Thus, the multi-channel decorrelator 600 effectively (when seen from the outside) receives N decorrelator input signals and provides, on the basis thereof, N′ decorrelator output signals, while the actual decorrelator core 630 only operates on a smaller number of signals (namely K downmixed decorrelator input signals 622a to 622k of the second set of K decorrelator input signals). Thus, the complexity of the multi-channel decorrelator 600 can be substantially reduced, when compared to conventional decorrelators, by performing a downmixing or “premixing” (which may advantageously be a linear premixing without any decorrelation functionality) at an input side of the decorrelation (or decorrelator core) 630 and by performing the upmixing or “postmixing” (for example, a linear upmixing without any additional decorrelation functionality) on the basis of the (original) output signals 632a to 632k′ of the decorrelation (decorrelator core) 630.
Moreover, it should be noted that the multi-channel decorrelator 600 can be supplemented by any of the features and functionalities described herein with respect to the multi-channel decorrelation and also with respect to the multi-channel audio decoders. It should be noted that the features described herein can be added to the multi-channel decorrelator 600 either individually or in combination, to thereby improve or enhance the multi-channel decorrelator 600.
It should be noted that a multi-channel decorrelator without complexity reduction can be derived from the above described multichannel decorrelator for K=N (and possibly K′=N′ or even K=N=K′=N′).
The multi-channel audio decoder 700 is configured to receive an encoded representation 710 and to provide, on the basis of thereof, at least two output signals 712, 714. The multi-channel audio decoder 700 comprises a multi-channel decorrelator 720, which may be substantially identical to the multi-channel decorrelator 600 according to
Moreover, it should be noted that the multi-channel audio decoder 700 comprises a particularly high efficiency when compared to conventional multi-channel audio decoders, since the multi-channel audio decoder 700 uses the high-efficiency multi-channel decorrelator 720.
The multi-channel audio encoder 800 comprises a downmix signal provider 820, which is configured to provide one or more downmix signals 822 on the basis of the at least two input audio signals 810, 812. The multi-channel audio encoder 800 also comprises a parameter provider 830 which is configured to provide one or more parameters 832 (for example, cross-correlation parameters or cross-covariance parameters, or inter-object-correlation parameters and/or object level difference parameters) on the basis of the input audio signals 810,812. Moreover, the multi-channel audio encoder 800 comprises a decorrelation complexity parameter provider 840 which is configured to provide a decorrelation complexity parameter 842 describing a complexity of a decorrelation to be used at the side of an audio decoder (which receives the encoded representation 814). The one or more downmix signals 822, the one or more parameters 832 and the decorrelation complexity parameter 842 are included into the encoded representation 814, advantageously in an encoded form.
However, it should be noted that the internal structure of the multi-channel audio encoder 800 (for example, the presence of the downmix signal provider 820, of the parameter provider 830 and of the decorrelation complexity parameter provider 840) should be considered as an example only. Different structures are possible as long as the functionality described herein is achieved.
Regarding the functionality of the multi-channel audio encoder 800, it should be noted that the multi-channel encoder provides an encoded representation 814, wherein the one or more downmix signals 822 and the one or more parameters 832 may be similar to, or equal to, downmix signals and parameters provided by conventional audio encoders (like, for example, conventional SAOC audio encoders or USAC audio encoders). However, the multi-channel audio encoder 800 is also configured to provide the decorrelation complexity parameter 842, which allows to determine a decorrelation complexity which is applied at the side of an audio decoder. Accordingly, the decorrelation complexity can be adapted to the audio content which is currently encoded. For example, it is possible to signal a desired decorrelation complexity, which corresponds to an achievable audio quality, in dependence on an encoder-sided knowledge about the characteristics of the input audio signals. For example, if it is found that spatial characteristics are important for an audio signal, a higher decorrelation complexity can be signaled, using the decorrelation complexity parameter 842, when compared to a case in which spatial characteristics are not so important. Alternatively, the usage of a high decorrelation complexity can be signaled using the decorrelation complexity parameter 842, if it is found that a passage of the audio content or the entire audio content is such that a high complexity decorrelation is necessitated at a side of an audio decoder for other reasons.
To summarize, the multi-channel audio encoder 800 provides for the possibility to control a multi-channel audio decoder, to use a decorrelation complexity which is adapted to signal characteristics or desired playback characteristics which can be set by the multi-channel audio encoder 800.
Moreover, it should be noted that the multi-channel audio encoder 800 may be supplemented by any of the features and functionalities described herein regarding a multi-channel audio encoder, either individually or in combination. For example, some or all of the features described herein with respect to multi-channel audio encoders can be added to the multi-channel audio encoder 800. Moreover, the multi-channel audio encoder 800 may be adapted for cooperation with the multi-channel audio decoders described herein.
The method 900 comprises premixing 910 a first set of N decorrelator input signals into a second set of K decorrelator input signals, wherein K is smaller than N. The method 900 also comprises providing 920 a first set of K′ decorrelator output signals on the basis of the second set of K decorrelator input signals. For example, the first set of K′ decorrelator output signals may be provided on the basis of the second set of K decorrelator input signals using a decorrelation, which may be performed, for example, using a decorrelator core or using a decorrelation algorithm. The method 900 further comprises postmixing 930 the first set of K′ decorrelator output signals into a second set to N′ decorrelator output signals, wherein N′ is larger than K′ (with N′ and K′ being integer numbers). Accordingly, the second set of N′ decorrelator output signals, which are the output of the method 900, may be provided on the basis of the first set of N decorrelator input signals, which are the input to the method 900.
It should be noted that the method 900 is based on the same considerations as the multi-channel decorrelator described above. Moreover, it should be noted that the method 900 may be supplemented by any of the features and functionalities described herein with respect to the multi-channel decorrelator (and also with respect to the multi-channel audio encoder, if applicable), either individually or taken in combination.
The method 1000 comprises providing 1010 at least two output audio signals 1014, 1016 on the basis of an encoded representation 1012. The method 1000 comprises providing 1020 a plurality of decorrelated signals on the basis of a plurality of decorrelator input signals in accordance with the method 900 according to
It should be noted that the method 1000 is based on the same considerations as the multi-channel audio decoder 700 according to
Also, it should be noted that the method 1000 can be supplemented by any of the features and functionalities described herein with respect to the multi-channel decoders, either individually or in combination.
The method 1100 comprises providing 1110 one or more downmix signals on the basis of the at least two input audio signals 1112, 1114. The method 1100 also comprises providing 1120 one or more parameters describing a relationship between the at least two input audio signals 1112, 1114. Furthermore, the method 1100 comprises providing 1130 a decorrelation complexity parameter describing a complexity of a decorrelation to be used at the side of an audio decoder. Accordingly, an encoded representation 1132 is provided on the basis of the at least two input audio signals 1112, 1114, wherein the encoded representation typically comprises the one or more downmix signals, the one or more parameters describing a relationship between the at least two input audio signals and the decorrelation complexity parameter in an encoded form.
It should be noted that the steps 1110, 1120, 1130 may be performed in parallel or in a different order in some embodiments according to the invention. Moreover, it should be noted that the method 1100 is based on the same considerations as the multi-channel audio encoder 800 according to
Recently, parametric techniques for the bitrate efficient transmission/storage of audio scenes containing multiple audio objects have been proposed in the field of audio coding (see, for example, references [BCC], [JSC], [SAOC], [SAOC1], [SAOC2]) and informed source separation (see, for example, references [ISS1], [ISS2], [ISS3], [ISS4], [ISS5], [ISS6]). These techniques aim at reconstructing a desired output audio scene or audio source object based on additional side information describing the transmitted/stored audio scene and/or source objects in the audio scene. This reconstruction takes place in the decoder using a parametric informed source separation scheme. Moreover, reference is also made to the so-called “MPEG Surround” concept, which is described, for example, in the international standard ISO/IEC 23003-1:2007. Moreover, reference is also made to the so-called “Spatial Audio Object Coding” which is described in the international standard ISO/IEC 23003-2:2010. Furthermore, reference is made to the so-called “Unified Speech and Audio Coding” concept, which is described in the international standard ISO/IEC 23003-3:2012. Concepts from these standards can be used in embodiments according to the invention, for example, in the multi-channel audio encoders mentioned herein and the multi-channel audio decoders mentioned herein, wherein some adaptations may be necessitated.
In the following, some background information will be described. In particular, an overview on parametric separation schemes will be provided, using the example of MPEG spatial audio object coding (SAOC) technology (see, for example, the reference [SAOC]). The mathematical properties of this method are considered.
13.1. Notation and Definitions
The following mathematical notation is applied in the current document:
size 2NUpmixCh×NSamples
Without loss of generality, in order to improve readability of equations, for all introduced variables the indices denoting time and frequency dependency are omitted in this document.
13.2. Parametric Separation Systems
General parametric separation systems aim to estimate a number of audio sources from a signal mixture (downmix) using auxiliary parameter information (like, for example, inter-channel correlation values, inter-channel level difference values, inter-object correlation values and/or object level difference information). A typical solution of this task is based on application of the minimum mean squared error (MMSE) estimation algorithms. The SAOC technology is one example of such parametric audio encoding/decoding systems.
An encoder 1310 receives a plurality of object signals 1312a, 1312b to 1312n. Moreover, the encoder 1310 also receives mixing parameters D, 1314, which may, for example, be downmix parameters. The encoder 1310 provides, on the basis thereof, one or more downmix signals 1316a, 1316b, and so on. Moreover, the encoder provides a side information 1318 The one or more downmix signals and the side information may, for example, be provided in an encoded form.
The encoder 1310 comprises a mixer 1320, which is typically configured to receive the object signals 1312a to 1312n and to combine (for example downmix) the object signals 1312a to 1312n into the one or more downmix signals 1316a, 1316b in dependence on the mixing parameters 1314. Moreover, the encoder comprises a side information estimator 1330, which is configured to derive the side information 1318 from the object signals 1312a to 1312n. For example, the side information estimator 1330 may be configured to derive the side information 1318 such that the side information describes a relationship between object signals, for example, a cross-correlation between object signals (which may be designated as “inter-object-correlation” IOC) and/or an information describing level differences between object signals (which may be designated as a “object level difference information” OLD).
The one or more downmix signals 1316a, 1316b and the side information 1318 may be stored and/or transmitted to a decoder 1350, which is indicated at reference numeral 1340.
The decoder 1350 receives the one or more downmix signals 1316a, 1316b and the side information 1318 (for example, in an encoded form) and provides, on the basis thereof, a plurality of output audio signals 1352a to 1352n. The decoder 1350 may also receive a user interaction information 1354, which may comprise one or more rendering parameters R (which may define a rendering matrix). The decoder 1350 comprises a parametric object separator 1360, a side information processor 1370 and a renderer 1380. The side information processor 1370 receives the side information 1318 and provides, on the basis thereof, a control information 1372 for the parametric object separator 1360. The parametric object separator 1360 provides a plurality of object signals 1362a to 1362n on the basis of the downmix signals 1360a, 1360b and the control information 1372, which is derived from the side information 1318 by the side information processor 1370. For example, the object separator may perform a decoding of the encoded downmix signals and an object separation. The renderer 1380 renders the reconstructed object signals 1362a to 1362n, to thereby obtain the output audio signals 1352a to 1352n.
In the following, the functionality of the MMSE based parameter downmix/upmix concept will be discussed.
The general parametric downmix/upmix processing is carried out in a time/frequency selective way and can be described as a sequence of the following steps:
Moreover, it should be noted that the functionalities described with respect to the encoder 1310 and the decoder 1350 may be used in the other audio encoders and audio decoders described herein as well.
13.3. Orthogonality Principle of Minimum Mean Squared Error Estimation
Orthogonality principle is one major property of MMSE estimators. Consider two Hilbert spaces W and V, with V spanned by a set of vectors yi, and a vector x∈W. If one wishes to find an estimate {circumflex over (x)}∈V which will approximate x as a linear combination of the vectors yi∈V, while minimizing the mean square error, then the error vector will be orthogonal on the space spanned by the vectors yi:
(x−{circumflex over (x)})yH=0,
As a consequence, the estimation error and the estimate itself are orthogonal:
(x−{circumflex over (x)}){circumflex over (x)}H=0.
Geometrically one could visualize this by the examples shown in
13.4. Parametric Reconstruction Error
Defining a matrix comprising N signals: X and denoting the estimation error with XError, the following identities can be formulated. The original signal can be represented as a sum of the parametric reconstruction {circumflex over (X)} and the reconstruction error XError as
X={circumflex over (X)}+XError.
Because of the orthogonality principle, the covariance matrix of the original signals EX=XXH can be formulated as a sum of the covariance matrix of the reconstructed signals {circumflex over (X)}{circumflex over (X)}H and the covariance matrix of the estimation errors XErrorXErrorH as
When the input objects X are not in the space spanned by the downmix channels (e.g. the number of downmix channels is less than the number of input signals) and the input objects cannot be represented as linear combinations of the downmix channels, the MMSE-based algorithms introduce reconstruction inaccuracy XErrorXErrorH.
13.5. Inter Object Correlation
In the auditory system, the cross-covariance (coherence/correlation) is closely related to the perception of envelopment, of being surrounded by the sound, and to the perceived width of a sound source. For example in SAOC based systems the Inter-Object Correlation (IOC) parameters are used for characterization of this property:
Let us consider an example of reproducing a sound source using two audio signals. If the IOC value is close to one, the sound is perceived as a well-localized point source. If the IOC value is close to zero, the perceived width of the sound source increases and for extreme cases it can even be perceived as two distinct sources [Blauert, Chapter 3].
13.6. Compensation for Reconstruction Inaccuracy
In the case of imperfect parametric reconstruction, the output signal may exhibit a lower energy compared to the original objects. The error in the diagonal elements of the covariance matrix may result in audible level differences and error in the off-diagonal elements in a distorted spatial sound image (compared with the ideal reference output). The proposed method has the purpose to solve this problem.
In the MPEG Surround (MPS), for example, this issue is treated only for some specific channel-based processing scenarios, namely, for mono/stereo downmix and limited static output configurations (e.g., mono, stereo, 5.1, 7.1, etc). In object-oriented technologies, like SAOC, which also uses mono/stereo downmix this problem is treated by applying the MPS post-processing rendering for 5.1 output configuration only.
The existing solutions are limited to standard output configurations and fixed number of input/output channels. Namely, they are realized as consequent application of several blocks implementing just “mono-to-stereo” (or “stereo-to-three”) channel decorrelation methods.
Therefore, a general solution (e.g., energy level and correlation properties correction method) for parametric reconstruction inaccuracy compensation is desired, which can be applied for a flexible number of downmix/output channels and arbitrary output configuration setups.
13.7. Conclusions
To conclude, an overview over the notation has been provided. Moreover, a parametric separation system has been described on which embodiments according to the invention are based. Moreover, it has been outlined that the orthogonality principle applies to minimum mean squared error estimation. Moreover, an equation for the computation of a covariance matrix EX has been provided which applies in the presence of a reconstruction error XError. Also, the relationship between the so-called inter-object correlation values and the elements of a covariance matrix EX has been provided, which may be applied, for example, in embodiments according to the invention to derive desired covariance characteristics (or correlation characteristics) from the inter-object correlation values (which may be included in the parametric side information), and possibly form the object level differences. Moreover, it has been outlined that the characteristics of reconstructed object signals may differ from desired characteristics because of an imperfect reconstruction. Moreover, it has been outlined that existing solutions to deal with the problem are limited to some specific output configurations and rely on a specific combination of standard blocks, which makes the conventional solutions inflexible.
14.1. Concept Overview
Embodiments according to the invention extend the MMSE parametric reconstruction methods used in parametric audio separation schemes with a decorrelation solution for an arbitrary number of downmix/upmix channels. Embodiments according to the invention, like, for example, the inventive apparatus and the inventive method, may compensate for the energy loss during a parametric reconstruction and restore the correlation properties of estimated objects.
The system according to
The parametric reconstruction system also comprises a transmission and/or storage of the one or more downmix signals 1516a, 1516b and of the side information 1518, wherein the transmission and/or storage is designated with 1540, and wherein the one or more downmix signals 1516a, 1516b and the side information 1518 (which may include parametric side information) may be encoded.
Moreover, the parametric reconstruction system according to
The parametric object separator 1560 is configured to receive the one or more downmix signals 1516a, 1516b and a control information 1572, which is provided by the side information processor 1570 on the basis of the side information 1518, and to provide, on the basis thereof, object signals 1562a to 1562n, which are also designated with X, and which may be considered as decoded audio signals. The control information 1572 may, for example, comprise un-mixing coefficients to be applied to downmix signals (for example, to decoded downmix signals derived from the encoded downmix signals 1516a, 1516b) within the parametric object separator to obtain reconstructed object signals (for example, the decoded audio signals 1562a to 1562n). The renderer 1580 renders the decoded audio signals 1562a to 1562n (which may be reconstructed object signals, and which may, for example, correspond to the input object signals 1512a to 1512n), to thereby obtain a plurality of rendered audio signals 1582a to 1582n. For example, the renderer 1580 may consider rendering parameters R, which may for example be provided by user interaction and which may, for example, define a rendering matrix. However, alternatively, the rendering parameters may be taken from the encoded representation (which may include the encoded downmix signals 1516a, 1516b and the encoded side information 1518).
The decorrelator 1590 is configured to receive the rendered audio signals 1582a to 1582n and to provide, on the basis thereof, decorrelated audio signals 1592a to 1592n, which are also designated with W. The mixer 1598 receives the rendered audio signals 1582a to 1582n and the decorrelated audio signals 1592a to 1592n, and combines the rendered audio signals 1582a to 1582n and the decorrelated audio signals 1592a to 1592n, to thereby obtain the output audio signals 1552a to 1552n. The mixer 1598 may also use control information 1574 which is derived by the side information processor 1570 from the encoded side information 1518, as will be described below.
14.2. Decorrelator Function
In the following, some details regarding the decorrelator 1590 will be described. However, it should be noted that different decorrelator concepts may be used, some of which will be described below.
In an embodiment, the decorrelator function w=Fdecorr({circumflex over (z)}) provides an output signal w that is orthogonal to the input signal {circumflex over (z)} (E{w{circumflex over (z)}H}=0). The output signal w has equal (to the input signal {circumflex over (z)}) spectral and temporal envelope properties (or at least similar properties). Moreover, signal w is perceived similarly and has the same (or similar) subjective quality as the input signal {circumflex over (z)} (see, for example, [SAOC2]).
In case of multiple input signals, it is beneficial if the decorrelation function produces multiple outputs that are mutually orthogonal (i.e., Wi=Fdecorr({circumflex over (Z)}i), such that Wi{circumflex over (Z)}jH=0 for all i and j, and WiWjH=0 for i≠j).
The exact specification for decorrelator function implementation is out of scope of this description. For example, the bank of several Infinite Impulse Response (IIR) filter based decorrelators specified in the MPEG Surround Standard can be utilized for decorrelation purposes [MPS].
The generic decorrelators described in this description are assumed to be ideal. This implies that (in addition to the perceptual requirements) the output of each decorrelator is orthogonal on its input and on the output of all other decorrelators. Therefore, for the given input {circumflex over (Z)} with covariance E{circumflex over (Z)}={circumflex over (Z)}{circumflex over (Z)}H and output W=Fdecorr({circumflex over (Z)}) the following properties of covariance matrices holds:
EW(i,i)=E{circumflex over (Z)}(i,i),EW(i,j)=0,for i≠j,{circumflex over (Z)}WH=W{circumflex over (Z)}H=0.
From these relationships, it follows that
({circumflex over (Z)}+W)({circumflex over (Z)}+W)H=E{circumflex over (Z)}+{circumflex over (Z)}WH+W{circumflex over (Z)}H+EW=E{circumflex over (Z)}+EW.
The decorrelator output W can be used to compensate for prediction inaccuracy in an MMSE estimator (remembering that the prediction error is orthogonal to the predicted signals) by using the predicted signals as the inputs.
One should still note that the prediction errors are not in a general case orthogonal among themselves. Thus, one aim of the inventive concept (e.g. method) is to create a mixture of the “dry” (i.e., decorrelator input) signal (e.g., rendered audio signals 1582a to 1582n) and “wet” (i.e., decorrelator output) signal (e.g., decorrelated audio signals 1592a to 1592n), such that the covariance matrix of the resulting mixture (e.g. output audio signals 1552a to 1552n) becomes similar to the covariance matrix of the desired output.
Moreover, it should be noted that a complexity reduction for the decorrelation unit may be used, which will be described in detail below, and which may bring along some imperfections of the decorrelated signal, which may, however, be acceptable.
14.3. Output Covariance Correction Using Decorrelated Signals
In the following, a concept will be described to adjust covariance characteristics of the output audio signals 1552a to 1552n to obtain a reasonably good hearing impression.
The proposed method for the output covariance error correction composes the output signal {tilde over (Z)}) (e.g. the output audio signals 1552a to 1552n) as a weighted sum of parametrically reconstructed signal {circumflex over (Z)} (e.g., the rendered audio signals 1582a to 1582n) and its decorrelated part W. This sum can be represented as follows
{tilde over (Z)}=P{circumflex over (Z)}+MW.
The mixing matrices P applied to the direct signal {circumflex over (Z)} and M applied to decorrelated signal W have the following structure (with N=NUpmixCh, wherein NUpmixCh designates a number of rendered audio signals, which may be equal to a number of output audio signals):
Applying notation for the combined matrix F=[P M] and signal
it yields:
{tilde over (Z)}=FS.
Using this representation, the covariance matrix E{tilde over (Z)} of of the output signal {tilde over (Z)} is defined as
E{tilde over (Z)}=FESFH.
The target covariance C of the ideally created rendered output scene is defined as
C=REXRH.
The mixing matrix F is computed such that the covariance matrix E{tilde over (Z)} of the final output approximates, or equals, the target covariance C as
E{tilde over (Z)}≈C.
The mixing matrix F is computed, for example, as a function of known quantities F=F(ES,EX,R) as
F=(U√{square root over (T)}UH)H(V√{square root over (Q−1)}VH),
where the matrices U, T and V, Q can be determined, for example, using Singular Value Decomposition (SVD) of the covariance matrices ES and C yielding
C=UTUH,ES=VQVH.
The prototype matrix H can be chosen according to the desired weightings for the direct and decorrelated signal paths.
For example, a possible prototype matrix H can be determined as
where ai,i2+bi,i2=1.
In the following, some mathematical derivations for the general matrix F structure will be provided.
In other words, the derivation of the mixing matrix F for a general solution will be described in the following.
The covariance matrices ES and C can be expressed using, e.g., Singular Value Decomposition (SVD) as
ES=VQVH,C=UTUH.
with T and Q being diagonal matrices with the singular values of C and ES respectively, and U and V being unitary matrices containing the corresponding singular vectors.
Note, that application of the Schur triangulation or Eigenvalue decomposition (instead of SVD) leads to similar results (or even identical results if the diagonal matrices Q and T are restricted to positive values).
Applying this decomposition to the requirement EZ≈C, it yields (at least approximately)
C=FESFH,
UTUH=FVQVHFH,
(U√{square root over (T)}UH)(U√{square root over (T)}UH)=F(V√{square root over (Q)}VH)(V√{square root over (Q)}VH)FH,
(U√{square root over (T)}UH)(U√{square root over (T)}UH)=(FV√{square root over (Q)}VH)(V√{square root over (Q)}VHFH),
(U√{square root over (T)}UH)(U√{square root over (T)}UH)=(FV√{square root over (Q)}VH)(FV√{square root over (Q)}VH)H.
In order to take care about the dimensionality of the covariance matrices, regularization is needed in some cases. For example, a prototype matrix H of size NUpmixCh×2NUpmixCh, with the property that HHH=IN
(U√{square root over (T)}UH)HHH(U√{square root over (T)}UH)=F(V√{square root over (Q)}VH)(√{square root over (Q)}VH)FH,
(U√{square root over (T)}UH)H=F(V√{square root over (Q)}VH).
It follows that mixing matrix F can be determined as
F=(U√{square root over (T)}UH)H(V√{square root over (Q−1)}VH).
The prototype matrix H is chosen according to the desired weightings for the direct and decorrelated signal paths. For example, a possible prototype matrix H can be determined as
where ai,i2+bi,i2=1.
Depending on the condition of the covariance matrix ES of the combined signals, the last equation may need to include some regularization, but otherwise it should be numerically stable.
To conclude, a concept has been described to derive the output audio signals (represented by matrix {tilde over (Z)}, or equivalently, by vector {tilde over (z)}) on the basis of the rendered audio signals (represented by matrix {circumflex over (Z)}, or equivalently, vector {circumflex over (z)}) and the decorrelated audio signals (represented by matrix W, or equivalently, vector w). As can be seen, two mixing matrices P and M of general matrix structure are commonly determined. For example, a combined matrix F, as defined above, may be determined, such that a covariance matrix E{circumflex over (Z)} of the output audio signals 1552a to 1562n approximates, or equals, a desired covariance (also designated as target covariance) C. The desired covariance matrix C may, for example, be derived on the basis of the knowledge of the rendering matrix R (which may be provided by user interaction, for example) and on the basis of a knowledge of the object covariance matrix EX, which may for example be derived on the basis of the encoded side information 1518. For example, the object covariance matrix EX may be derived using the inter-object correlation values IOC, which are described above, and which may be included in the encoded side information 1518. Thus, the target covariance matrix C may, for example, be provided by the side information processor 1570 as the information 1574, or as part of the information 1574.
However, alternatively, the side information processor 1570 may also directly provide the mixing matrix F as the information 1574 to the mixer 1598.
Moreover, a computation rule for the mixing matrix F has been described, which uses a singular value decomposition. However, it should be noted that there are some degrees of freedom, since the entries ai,i and bi,i of the prototype matrix H may be chosen. Advantageously, the entries of the prototype matrix H are chosen to be somewhere between 0 and 1. If values ai,i are chosen to be closer to one, there will be a significant mixing of rendered output audio signals, while the impact of the decorrelated audio signals is comparatively small, which may be desirable in some situations. However, in some other situations it may be more desirable to have a comparatively large impact of the decorrelated audio signals, while there is only a weak mixing between rendered audio signals. In this case, values bi,i are typically chosen to be larger than ai,i. Thus, the decoder 1550 can be adapted to the requirements by appropriately choosing the entries of the prototype matrix H.
14.4. Simplified Methods for Output Covariance Correction
In this section, two alternative structures for the mixing matrix F mentioned above are described along with exemplary algorithms for determining its values. The two alternatives are designed to for different input content (e.g. audio content):
14.4.1. Covariance Adjustment Method (A)
Taking in account that the signal {circumflex over (Z)} (e.g., the rendered audio signals 1582a to 1582n) are already optimal in the MMSE-sense, it is usually not advisable to modify the parametric reconstructions {circumflex over (Z)} (e.g., the output audio signals 1552a to 1552n) in order to improve the covariance properties of the output {tilde over (Z)} because this may affect the separation quality.
If only the mixture of the decorrelated signals W is manipulated, the mixing matrix P can be reduced to an identity matrix (or a multiple thereof). Thus, this simplified method can be described by setting
The final output of the system can be represented as
{tilde over (Z)}={circumflex over (Z)}+MW.
Consequently the final output covariance of the system can be represented as:
E{tilde over (Z)}=E{circumflex over (Z)}+MEWMH
The difference ΔE between the ideal (or desired) output covariance matrix C and the covariance matrix E{circumflex over (Z)} of the rendered parametric reconstruction (e.g., of the rendered audio signals) is given by
ΔE=C−E{circumflex over (Z)}.
Therefore, mixing matrix M is determined such that
ΔE≈MEWMH.
The mixing matrix M is computed such that the covariance matrix of the mixed decorrelated signals MW equals or approximates the covariance difference between the desired covariance and the covariance of the dry signals (e.g., of the rendered audio signals). Consequently the covariance of the final output will approximate the target covariance EZ≈C:
M=(U√{square root over (T)}UH)(V√{square root over (Q−1)}VH).
where the matrices U, T and V, Q can be determined, for example, using Singular Value Decomposition (SVD) of the covariance matrices ΔE and EW yielding
ΔE=UTUH,EW=VQVH.
This approach ensures good cross-correlation reconstruction maximizing use of the dry output (e.g., of the rendered audio signals 1582a to 1582n) and utilizes freedom of mixing of decorrelated signals only. In other words, there is no mixing between different rendered audio signals allowed when combining the rendered audio signals (or a scaled version thereof) with the one or more decorrelated audio signals. However, it is allowed that a given decorrelated signal is combined, with a same or different scaling, with a plurality of rendered audio signals, or a scaled version thereof, in order to adjust cross-correlation characteristics or cross-covariance characteristics of the output audio signals. The combination is defined, for example, by the matrix M as defined here.
In the following, some mathematical derivations for the restricted matrix F structure will be provided.
In other words, the derivation of the mixing matrix M for the simplified method “A” will be explained.
The covariance matrices ΔE and EW can be expressed using, e.g., Singular Value Decomposition (SVD) as
ΔE=UTUH,EW=VQVH.
with T and Q being diagonal matrices with the singular values of ΔE and EW respectively, and U and V being unitary matrices containing the corresponding singular vectors.
Note, that application of the Schur triangulation or Eigenvalue decomposition (instead of SVD) leads to similar results (or even identical results if the diagonal matrices Q and T are restricted to positive values).
Applying this decomposition to the requirement EZ≈C, it yields (at least approximately)
ΔE=MEWMH,
UTUH=MVQVHMH,
(U√{square root over (T)}UH)(U√{square root over (T)}UH)=M(V√{square root over (Q)}VH)(V√{square root over (Q)}VH)MH,
(U√{square root over (T)}UH)(U√{square root over (T)}UH)=(MV√{square root over (Q)}VH)(V√{square root over (Q)}VHMH),
(U√{square root over (T)}UH)(U√{square root over (T)}UH)H=(MV√{square root over (Q)}VH)(MV√{square root over (Q)}VH)H,
(U√{square root over (T)}UH)=M(V√{square root over (Q)}VH).
Noting that both sides of the equation represent a square of a matrix, we drop the squaring, and solve for the full matrix M.
It follows that mixing matrix M can be determined as
M=(U√{square root over (T)}UH)(V√{square root over (Q−1)}VH).
This method can be derived from the general method by setting the prototype matrix H as follows
Depending on the condition of the covariance matrix EW of the wet signals, the last equation may need to include some regularization, but otherwise it should be numerically stable.
14.4.2. Energy Compensation Method (B)
Sometimes (depending on the application scenario) is not desired to allow mixing of the parametric reconstructions (e.g., of the rendered audio signals) or the decorrelated signals, but to individually mix each parametrically reconstructed signal (e.g., rendered audio signal) with its own decorrelated signal only.
In order to achieve this requirement, an additional constraint should be introduced to the simplified method “A”. Now, the mixing matrix M of the wet signals (decorrelated signals) is necessitated to have a diagonal form:
The main goal of this approach is to use decorrelated signals to compensate for the loss of energy in the parametric reconstruction (e.g., rendered audio signal), while the off-diagonal modification of the covariance matrix of the output signal is ignored, i.e., there is no direct handling of the cross-correlations. Therefore, no cross-leakage between the output objects/channels (e.g., between the rendered audio signals) is introduced in the application of the decorrelated signals.
As a result, only the main diagonal of the target covariance matrix (or desired covariance matrix) can be reached, and the off-diagonals are on the mercy of the accuracy of the parametric reconstruction and the added decorrelated signals. This method is most suitable for object-only based applications, in which the signals can be considered as uncorrelated.
The final output of the method (e.g. the output audio signals) is given by {tilde over (Z)}={circumflex over (Z)}+MW with a diagonal matrix M computed such that the covariance matrix entries corresponding to the energies of the reconstructed signals E{tilde over (Z)}(i,i) are equal with the desired energies
E{tilde over (Z)}(i,i)=C(i,i).
C may be determined as explained above for the general case.
For example, the mixing matrix M can be directly derived by dividing the desired energies of the compensation signals (differences between the desired energies (which may be described by diagonal elements of the cross-covariance matrix C) and the energies of the parametric reconstructions (which may be determined by the audio decoder)) with the energies of the decorrelated signals (which may be determined by the audio decoder):
wherein λDec is a non-negative threshold used to limit the amount of decorrelated component added to the output signals (e.g., λDec=4).
It should be noted that the energies can be reconstructed parametrically (for example, using OLDs, IOCs and rendering coefficients) or may be actually computed by the decoder (which is typically more computationally expensive).
This method can be derived from the general method by setting the prototype matrix H as follows:
This method maximizes the use of the dry rendered outputs explicitly. The method is equivalent with the simplification “A” when the covariance matrices have no off-diagonal entries.
This method has a reduced computational complexity.
However, it should be noted that the energy compensation method, doesn't necessarily imply that the cross-correlation terms are not modified. This holds only if we use ideal decorrelators and no complexity reduction for the decorrelation unit. The idea of the method is to recover the energy and ignore the modifications in the cross terms (the changes in the cross-terms will not modify substantially the correlation properties and will not affect the overall spatial impression).
14.5. Requirements for the Mixing Matrix F
In the following, it will be explained that the mixing matrix F, a derivation of which has been described in sections 14.3 and 14.4, fulfills requirements to avoid degradations.
In order to avoid degradations in the output, any method for compensating for the parametric reconstruction errors should produce a result with the following property: if the rendering matrix equals the downmix matrix then the output channels should equal (or at least approximate) the downmix channels. The proposed model fulfills this property. If the rendering matrix is equal with the downmix matrix R=D, the parametric reconstruction is given by
{circumflex over (Z)}=R{circumflex over (X)}=D{circumflex over (X)}=DGY=DEDH(DEDH)−1Y≈Y,
and the desired covariance matrix will be
C=REXRH=DEXDH=EY.
Therefore the equation to be solved for obtaining the mixing matrix F is
where 0N
This means that the decorrelated signals will have zero-weight in the summing, and the final output will be given by the dry signals, which are identical with the downmix signals
{tilde over (Z)}=P{circumflex over (Z)}+MW={circumflex over (Z)}≈Y.
As a result, the given requirement for the system output to equal the downmix signal in this rendering scenario is fulfilled.
14.6. Estimation of Signal Covariance Matrix ES
To obtain the mixing matrix F the knowledge of the covariance matrix ES of the combined signals S is necessitated or at least desirable.
In principle, it is possible to estimate the covariance matrix ES directly from the available signals (namely, from parametric reconstruction {circumflex over (Z)} and the decorrelator output W). Although this approach may lead to more accurate results, it is may not be practical because of the associated computational complexity. The proposed methods use parametric approximations of the covariance matrix ES.
The general structure of the covariance matrix ES can be represented as
where the matrix E{circumflex over (Z)}W is cross-covariance between the direct {circumflex over (Z)} and decorrelated W signals.
Assuming that the decorrelators are ideal (i.e., energy-preserving, the outputs being orthogonal to the inputs, and all outputs being mutually orthogonal), the covariance matrix ES can be expressed using the simplified form as
The covariance matrix E{circumflex over (Z)} of the parametrically reconstructed signal Z can be determined parametrically as
E{circumflex over (Z)}=RE{circumflex over (X)}RH=RGDEXDHGHRH.
The covariance matrix EW of the decorrelated signal W is assumed to fulfill the mutual orthogonality property and to contain only the diagonal elements of E{circumflex over (Z)} as follows
If the assumption of mutual orthogonality and/or energy-preservation is violated (e.g., in the case when the number of decorrelators available is smaller than the number of signals to be decorrelated), then the covariance matrix EW can be estimated as
EW=Mpost[matdiag(MpreE{circumflex over (Z)}MpreH)]MpostH.
In the following, it will be described how the complexity of the decorrelators used in embodiments according to the present invention can be reduced.
It should be noted that decorrelator function implementation is often computationally complex. In some applications (e.g., portable decoder solutions) limitations on the number of decorrelators may need to be introduced due to the restricted computational resources. This section provides a description of means for reduction of decorrelator unit complexity by controlling the number of applied decorrelators (or decorrelations). The decorrelation unit interface is depicted in
However,
The decorrelator 1700 comprises a premixer (or equivalently, a premixing functionality) 1720 which is configured to receive the first set of N decorrelator input signals 1710a to 1710n and to provide, on the basis thereof, a second set of K decorrelator input signals 1722a to 1722k. For example, the premixer 1720 may perform a so-called “premixing” or “downmixing” to derive the second set of K decorrelator input signals 1722a to 1722k on the basis of the first set of N decorrelator input signals 1710a to 1710n. For example, the K signals of the second set of K decorrelator input signals 1722a to 1722k may be represented using a matrix {circumflex over (Z)}mix.
The decorrelation unit (or, equivalently, multi-channel decorrelator) 1700 also comprises a decorrelator core 1730, which is configured to receive the K signals of the second set of decorrelator input signals 1722a to 1722k, and to provide, on the basis thereof, K decorrelator output signals which constitute a first set of decorrelator output signals 1732a to 1732k. For example, the decorrelator core 1730 may comprise K individual decorrelators (or decorrelation functions), wherein each of the individual decorrelators (or decorrelation functions) provides one of the decorrelator output signals of the first set of K decorrelator output signals 1732a to 1732k on the basis of a corresponding decorrelator input signal of the second set of K decorrelator input signals 1722a to 1722k. Alternatively, a given decorrelator, or decorrelation function, may be applied K times, such that each of the decorrelator output signals of the first set of K decorrelator output signals 1732a to 1732k is based on a single one of the decorrelator input signals of the second set of K decorrelator input signals 1722a to 1722k.
The decorrelation unit 1700 also comprises a postmixer 1740, which is configured to receive the K decorrelator output signals 1732a to 1732k of the first set of decorrelator output signals and to provide, on the basis thereof, the N signals 1712a to 1712n of the second set of decorrelator output signals (which constitute the “external” decorrelator output signals).
It should be noted that the premixer 1720 may advantageously perform a linear mixing operation, which may be described by a premixing matrix Mpre. Moreover, the postmixer 1740 may perform a linear mixing (or upmixing) operation, which may be represented by a postmixing matrix Mpost, to derive the N decorrelator output signals 1712a to 1712n of the second set of decorrelator output signals from the first set of K decorrelator output signals 1732a to 1732k (i.e., from the output signals of the decorrelator core 1730).
The main idea of the proposed method and apparatus is to reduce the number of input signals to the decorrelators (or to the decorrelator core) from N to K by:
The premixing matrix Mpre can be constructed based on the downmix/rendering/correlation/etc information such that the matrix product (MpreMpreH) becomes well-conditioned (with respect to inversion operation). The postmixing matrix can be computed as
Mpost≈MpreH(MpreMpreH)−1.
Even though the covariance matrix of the intermediate decorrelated signals {tilde over (S)} (or {circumflex over (Z)}mixdec) is diagonal (assuming ideal decorrelators), the covariance matrix of the final decorrelated signals W will quite likely not be diagonal anymore when using this kind of a processing. Therefore, the covariance matrix may be to be estimated using the mixing matrices as
EW=Mpost[matdiag(MpreE{circumflex over (Z)}MpreH)]MpostH
The number of used decorrelators (or individual decorrelations), K, is not specified and is dependent on the desired computational complexity and available decorrelators. Its value can be varied from N (highest computational complexity) down to 1 (lowest computational complexity).
The number of input signals to the decorrelator unit, N, is arbitrary and the proposed method supports any number of input signals, independent on the rendering configuration of the system.
For example in applications using 3D audio content, with high number of output channels, depending on the output configuration one possible expression for the premixing matrix Mpre is described below.
In the following, it will be described how the premixing, which is performed by the premixer 1720 (and, consequently, the postmixing, which is performed by the postmixer 1740) is adjusted if the decorrelation unit 1700 is used in a multi-channel audio decoder, wherein the decorrelator input signals 1710a to 1710n of the first set of decorrelator input signals are associated with different spatial positions of an audio scene.
For this purpose,
In the table 1800 of
However, it should be noted that one low frequency effect loudspeaker is used for output formats O-5.1, O-7.1, O-8.1 and O-10.1, and that two low frequency effect loudspeakers (LFE1, LFE2) are used for output format O-22.2. Moreover, it should be noted that, in one embodiment, one rendered audio signal (for example, one of the rendered audio signals 1582a to 1582n) is associated with each of the loudspeakers, except for the one or more low frequency effect loudspeakers. Accordingly, two rendered audio signals are associated with the two loudspeakers used according to the O-2.0 format, five rendered audio signals are associated with the five non-low-frequency-effect loudspeakers if the O-5.1 format is used, seven rendered audio signals are associated with seven non-low-frequency-effect loudspeakers if the O-7.1 format is used, eight rendered audio signals are associated with the eight non-low-frequency-effect loudspeakers if the O-8.1 format is used, ten rendered audio signals are associated with the ten non-low-frequency-effect loudspeakers if the O-10.1 format is used, and 22 rendered audio signals are associated with the 22 non-low-frequency-effect loudspeakers if the O-22.2 format is used.
However, it is often desirable to use a smaller number of (individual) decorrelators (of the decorrelator core), as mentioned above. In the following, it will be described how the number of decorrelators can be reduced flexibly when the O-22.2 output format is used by a multi-channel audio decoder, such that there are 22 rendered audio signals 1582a to 1582n (which may be represented by a matrix {circumflex over (Z)}, or by a vector {circumflex over (z)}).
In the following, the functionality defined by the premixing Mpre of
Taking reference now to
Taking reference now to
Taking reference to
Taking reference now to
For example,
Similarly,
Similarly,
Finally,
To summarize, the premixing matrices according to
Taking reference now to
A third row 2414 represents a third group of positions. It should be noted that positions “CH_M _L030” and “CH_L_L045” are spatially adjacent positions and comprise similar azimuth (or, equivalently, similar horizontal position) and similar elevation (or, equivalently, similar vertical position). The same holds for positions “CH_M_R030” and “CH_L_R045”. Moreover, the positions of the third group of positions form a quadruple of positions, wherein positions “CH_M_L030” and “CH_L_L045” are spatially adjacent, and symmetrical with respect to a center plane of the audio scene, to positions “CH_M_R030” and “CH_L_R045”.
A fourth row 2416 represents four additional positions, which have similar characteristics when compared to the first four positions of the second row, and which form a symmetrical quadruple of positions.
A fifth row 2418 represents another quadruple of symmetrical positions “CH_M_L060”, “CH_U_L045”, “CH_M_R060” and “CH_U_R045”.
Moreover, it should be noted that rendered audio signals associated with the positions of the different groups of positions may be combined more and more with decreasing number of decorrelators. For example, in the presence of eleven individual decorrelators in a multi-channel decorrelator, rendered audio signals associated with positions in the first and second column may be combined for each group. In addition, rendered audio signals associated with the positions represented in a third and a fourth column may be combined for each group. Furthermore, rendered audio signals associated with the positions shown in the fifth and sixth column may be combined for the second group. Accordingly, eleven downmix decorrelator input signals (which are input into the individual decorrelators) may be obtained. However, if it is desired to have less individual decorrelators, rendered audio signals associated with the positions shown in columns 1 to 4 may be combined for one or more of the groups. Also, rendered audio signals associated with all positions of the second group may be combined, if it is desired to further reduce a number of individual decorrelators.
To summarize, the signals fed to the output layout (for example, to the speakers) have horizontal and vertical dependencies, that should be preserved during the decorrelation process. Therefore, the mixing coefficients are computed such that the channels corresponding to different loudspeaker groups are not mixed together.
Depending on the number of available decorrelators, or the desired level of decorrelation, in each group first are mixed together the vertical pairs (between the middle layer and the upper layer or between the middle layer and the lower layer). Second, the horizontal pairs (between left and right) or remaining vertical pairs are mixed together. For example, in group three, first the channels in the left vertical pair (“CH_M_L030” and “CH_L_L045”), and in the right vertical pair (“CH_M_R030” and “CH_L_R045”), are mixed together, reducing in this way the number of necessitated decorrelators for this group from four to two. If it is desired to reduce even more the number of decorrelators, the obtained horizontal pair is downmixed to only one channel, and the number of necessitated decorrelators for this group is reduced from four to one.
Based on the presented mixing rules, the tables mentioned above (for example, shown in
In the case when the SAOC decoder (or, more generally, the multi-channel audio decoder) is used together with an external secondary renderer/format converter, the following changes to the proposed concept (method or apparatus) may be used:
Using an external format converter, the SAOC internal renderer will pre-render to an intermediate configuration (e.g., the configuration with the highest number of loudspeakers).
To conclude, in some embodiments an information about which of the output audio signals are mixed together in an external renderer or format converter are used to determine the premixing matrix Mpre, such that the premixing matrix defines a combination of such decorrelator input signals (of the first set of decorrelator input signals) which are actually combined in the external renderer. Thus, information received from the external renderer/format converter (which receives the output audio signals of the multi-channel decoder) is used to select or adjust the premixing matrix (for example, when the internal rendering matrix of the multi-channel audio decoder is set to identity, or initialized with the mixing coefficients derived from an intermediate rendering configuration), and the external renderer/format converter is connected to receive the output audio signals as mentioned above with respect to the multi-channel audio decoder.
In the following, it will be described which additional signaling information can be used in a bitstream (or, equivalently, in an encoded representation of the audio content). In embodiments according to the invention, the decorrelation method may be signaled into the bitstream for ensuring a desired quality level. In this way, the user (or an audio encoder) has more flexibility to select the method based on the content. For this purpose, the MPEG SAOC bitstream syntax can be, for example, extended with two bits for specifying the used decorrelation method and/or two bits for specifying the configuration (or complexity).
Energy compensation mode uses the method described in section 14.4.2, limited covariance adjustment mode uses the method described in section 14.4.1, and general covariance adjustment mode uses the method described in section 14.3.
Taking reference now to
An example of decorrelation configurations (which may, for example, be designated as decorrelation levels”) is given in the table of
To summarize, the decorrelation method can be determined at the decoder side based on the computational power and an available number of decorrelators. In addition, selection of the number of decorrelators may be made at the encoder side and signaled using a bitstream parameter.
Accordingly, both the method how the decorrelated audio signals are applied, to obtain the output audio signals, and the complexity for the provision of the decorrelated signals can be controlled from the side of an audio encoder using the bitstream parameters shown in
It should be noted that it is one of the purposes of the introduced methods to restore audio cues, which are of greater importance for human perception of an audio scene. Embodiments according to the invention improve a reconstruction accuracy of energy level and correlation properties and therefore increase perceptual audio quality of the final output signal. Embodiments according to the invention can be applied for an arbitrary number of downmix/upmix channels. Moreover, the methods and apparatuses described herein can be combined with existing parametric source separation algorithms. Embodiments according to the invention allow to control computational complexity of the system by setting restrictions on the number of applied decorrelator functions. Embodiments according to the invention can lead to a simplification of the object-based parametric construction algorithms like SAOC by removing an MPS transcoding step.
In the following, an audio encoding/decoding environment will be described in which concepts according to the present invention can be applied.
A 3D audio codec system, in which concepts according to the present invention can be used, is based on an MPEG-D USAC codec for coding of channel and object signals to increase the efficiency for coding a large amount of objects. MPEG-SAOC technology has been adapted. Three types of renderers perform the tasks of rendering objects to channels, rendering channels to headphones or rendering channels to different loudspeaker setups. When object signals are explicitly transmitted or parametrically encoded using SAOC, the corresponding object metadata information is compressed and multiplexed into the 3D audio stream.
Taking reference now to
Some details regarding the individual components of the audio encoder 2900 will be described below.
Taking reference now to
In the following, some details regarding the components of the audio encoder 2900 and of the audio decoder 3000 will be described.
19.1. Pre-Renderer/Mixer
The pre-renderer/mixer 2910 can be optionally used to convert a channel plus object input scene into a channel scene before encoding. Functionally, it may, for example, be identical to the object renderer/mixer described below.
Pre-rendering of objects may, for example, ensure a deterministic signal entropy at the encoder input that is basically independent of the number of simultaneously active object signals.
Wth pre-rendering of objects, no object metadata transmission is necessitated.
Discrete object signals are rendered to the channel layout that the encoder is configured to use, the weights of the objects for each channel are obtained from the associated object metadata (OAM) 1952.
19.2. USAC Core Codec
The core codec 2930, 3020 for loudspeaker-channel signals, discrete object signals, object downmix signals and pre-rendered signals is based on MPEG-D USAC technology. It handles decoding of the multitude of signals by creating channel- and object-mapping information based on the geometric and semantic information of the input channel and object assignment. This mapping information describes, how input channels and objects are mapped to USAC channel elements (CPEs, SCEs, LFEs) and the corresponding information is transmitted to the decoder.
All additional payloads like SAOC data or object metadata have been passed through extension elements and have been considered in the encoders rate control. Decoding of objects is possible in different ways, dependent on the rate/distortion requirements and the interactivity requirements for the renderer. The following object coding variants are possible:
19.3. SAOC
The SAOC encoder 2940 and the SAOC decoder 3060 for object signals are based on MPEG SAOC technology. The system is capable of recreating, modifying and rendering a number of audio objects based on a smaller number of transmitted channels and additional parametric data (object level differences OLDs, inter-object correlations IOCs, downmix gains DMGs). The additional parametric data exhibits a significantly lower data rate than necessitated for transmitted all objects individually, making decoding very efficient. The SAOC encoder takes as input the object/channel signals as monophonic waveforms and outputs the parametric information (which is packed into the 3D audio bitstream 2932, 3010) and the SAOC transport channels (which are encoded using single channel elements and transmitted). The SAOC decoder 3000 reconstructs the object/channel signals from the decoded SAOC transport channels 3028 and parametric information 3030, and generates the output audio scene based on the reproduction layout, the decompressed object metadata information and optionally on the user interaction information.
19.4. Object Metadata Codec
For each object, the associated metadata that specifies the geometrical position and volume of the object in 3D space is efficiently coded by quantization of the object properties in time and space. The compressed object metadata cOAM 2954, 3032 is transmitted to the receiver as side information.
19.5. Object Renderer/Mixer
The object renderer utilizes the decompressed object metadata OAM 3044 to generate object waveforms according to the given reproduction format. Each object is rendered to certain output channels according to its metadata. The output of this block results from the sum of the partial results.
If both channel based content as well as discrete/parametric objects are decoded, the channel based waveforms and the rendered object waveforms are mixed before outputting the resulting waveforms (or before feeding them to a post-processor module like the binaural renderer or the loudspeaker renderer module).
19.6. Binaural Renderer
The binaural renderer module 3080 produces a binaural downmix of the multi-channel audio material, such that each input channel is represented by a virtual sound source. The processing is conducted frame-wise in QMF domain. The binauralization is based on measured binaural room impulse responses.
19.7. Loudspeaker Renderer/Format Conversion
The loudspeaker renderer 3090 converts between the transmitted channel configuration and the desired reproduction format. It is thus called “format converter” in the following. The format converter performs conversions to lower numbers of output channels, i.e. it creates downmixes. The system automatically generates optimized downmix matrices for the given combination of input and output formats and applies these matrices in a downmix process. The format converter allows for standard loudspeaker configurations as well as for random configurations with non-standard loudspeaker positions.
As can be seen, the format converter 3100 receives mixer output signals 3110, for example the mixed channel signals 3072, and provides loudspeaker signals 3112, for example the speaker signals 3016. The format converter comprises a downmix process 3120 in the QMF domain and a downmix configurator 3130, wherein the downmix configurator provides configuration information for the downmix process 3020 on the basis of a mixer output layout information 3032 and a reproduction layout information 3034.
19.8. General Remarks
Moreover, it should be noted that the concepts described herein, for example, the audio decoder 100, the audio encoder 200, the multi-channel decorrelator 600, the multi-channel audio decoder 700, the audio encoder 800 or the audio decoder 1550 can be used within the audio encoder 2900 and/or within the audio decoder 3000. For example, the audio encoders/decoders mentioned above may be used as part of the SAOC encoder 2940 and/or as a part of the SAOC decoder 3060. However, the concepts mentioned above may also be used at other positions of the 3D audio decoder 3000 and/or of the audio encoder 2900.
Naturally, the methods mentioned above may also be used in concepts for encoding or decoding audio information according to
20.1 Introduction
In the following, another embodiment according to the present invention will be described.
The downmix processor 3100 comprises an unmixer 3110, a renderer 3120, a combiner 3130 and a multi-channel decorrelator 3140. The renderer provides rendered audio signals Ydry to the combiner 3130 and to the multichannel decorrelator 3140. The multichannel decorrelator comprises a premixer 3150, which receives the rendered audio signals (which may be considered as a first set of decorrelator input signals) and provides, on the basis thereof, a premixed second set of decorrelator input signals to a decorrelator core 3160. The decorrelator core provides a first set of decorrelator output signals on the basis of the second set of decorrelator input signals for usage by a postmixer 3170. the postmixer postmixes (or upmixes) the decorrelator output signals provided by the decorrelator core 3160, to obtain a postmixed second set of decorrelator output signals, which is provided to the combiner 3130.
The renderer 3130 may, for example, apply a matrix R for the rendering, the premixer may, for example, apply a matrix Mpre for the premixing, the postmixer may, for example, apply a matrix Mpost for the postmixing, and the combiner may, for example, apply a matrix P for the combining.
It should be noted that the downmix processor 3100, or individual components or functionalities thereof, may be used in the audio decoders described herein. Moreover, it should be noted that the downmix processor may be supplemented by any of the features and functionalities described herein.
20.2 SAOC 3D processing
The hybrid filterbank described in ISO/IEC 23003-1:2007 is applied. The dequantization of the DMG, OLD, IOC parameters follows the same rules as defined in 7.1.2 of ISO/IEC 23003-2:2010.
20.2.1 Signals and Parameters
The audio signals are defined for every time slot n and every hybrid subband k. The corresponding SAOC 3D parameters are defined for each parameter time slot l and processing band m. The subsequent mapping between the hybrid and parameter domain is specified by Table A.31 of ISO/IEC 23003-1:2007. Hence, all calculations are performed with respect to the certain time/band indices and the corresponding dimensionalities are implied for each introduced variable.
The data available at the SAOC 3D decoder consists of the multi-channel downmix signal X, the covariance matrix E, the rendering matrix R and downmix matrix D.
20.2.1.1 Object Parameters
The covariance matrix E of size N×N with elements ei,i represents an approximation of the original signal covariance matrix E≈SS* and is obtained from the OLD and IOC parameters as:
ei,j=√{square root over (OLDiOLDj)}IOCi,j.
Here, the dequantized object parameters are obtained as:
OLDi=DOLD(i,l,m),IOCi,j=DIOC(i,j,l,m).
20.2.1.3 Downmix Matrix
The downmix matrix D applied to the input audio signals S determines the downmix signal as X=DS. The downmix matrix D of size Ndmx×N is obtained as:
D=DdmxDpremix.
The matrix Ddmx and matrix Dpremix have different sizes depending on the processing mode. The matrix Ddmx is obtained from the DMG parameters as:
Here, the dequantized downmix parameters are obtained as:
DMGi,j=DDMG(i,j,l).
20.2.1.3.1 Direct Mode
In case of direct mode, no premixing is used. The matrix Dpremix has the size N×N and is given by: Dpremix=I. The matrix Ddmx has size Ndmx×N and is obtained from the DMG parameters according to 20.2.1.3.
20.2.1.3.2 Premixing Mode
In case of premixing mode the matrix Dpremix has size (Nch+Npremix)×N and is given by:
where the premixing matrix A of size Npremix×Nobj is received as an input to the SAOC 3D decoder, from the object renderer.
The matrix Ddmx has size Ndmx×(Nch+Npremix) and is obtained from the DMG parameters according to 20.2.1.3
2.2.1.2 Rendering Matrix
The rendering matrix R applied to the input audio signals S determines the target rendered output as Y=RS. The rendering matrix R of size Nout×N is given by
R=(RchRobj),
where Rch of size Nout×Nch represents the rendering matrix associated with the input channels and Robj of size Nout×Nobj represents the rendering matrix associated with the input objects.
20.2.1.4 Target Output Covariance Matrix
The covariance matrix C of size Nout×Nout with elements ci,j represents an approximation of the target output signal covariance matrix C≈YY* and is obtained from the covariance matrix E and the rendering matrix R:
C=RER*.
20.2.2 Decoding
The method for obtaining an output signal using SAOC 3D parameters and rendering information is described. The SAOC 3D decoder my, for example, and consist of the SAOC 3D parameter processor and the SAOC 3D downmix processor.
20.2.2.1 Downmix Processor
The output signal of the downmix processor (represented in the hybrid QMF domain) is fed into the corresponding synthesis filterbank as described in ISO/IEC 23003-1:2007 yielding the final output of the SAOC 3D decoder. A detailed structure of the downmix processor is depicted in
The output signal Ŷ is computed from the multi-channel downmix signal X and the decorrelated multi-channel signal Xd as:
Ŷ=PdryRUX+PwetMpostXd,
where U represents the parametric unmixing matrix and is defined in 20.2.2.1.1 and 20.2.2.1.2.
The decorrelated multi-channel signal Xd is computed according to 20.2.3.
Xd=decorrFunc(MpreYdry).
The mixing matrix P=(Pdry Pwet) is described in 20.2.3. The matrices Mpre for different output configuration are given in
Mpost=Mpre*(MpreMpre*)−1.
The decoding mode is controlled by the bitstream element bsNumSaocDmxObjects, as shown in
20.2.2.1.1 Combined Decoding Mode
In case of combined decoding mode the parametric unmixing matrix U is given by:
U=ED*J.
The matrix J of size Ndmx×Ndmx is given by J≈Δ−1 with Δ=DED*.
20.2.2.1.2 Independent Decoding Mode
In case of independent decoding mode the unmixing matrix U is given by:
where Uch=EchDch*Jch and Uobj=EobjDobj*Jobj.
The channel based covariance matrix Ech of size Nch×Nch and the object based covariance matrix Eobj of size Nobj×Nobj are obtained from the covariance matrix E by selecting only the corresponding diagonal blocks:
where the matrix Ech,obj=(Eobj,ch)* represents the cross-covariance matrix between the input channels and input objects and is not required to be calculated.
The channel based downmix matrix Dch of size Nchdmx×Nch and the object based downmix matrix Dobj of size Nobjdmx×Nobj are obtained from the downmix matrix D by selecting only the corresponding diagonal blocks:
The matrix Jch≈(DchEchDch*)−1 of size Nchdmx×Nchdmx is derived accordingly to 20.2.2.1.4 for Δ=DchEchDch*.
The matrix Jobj≈(DobjEobjDobj*)−1 of size Nobjdmx×Nobjdmx is derived accordingly to 20.2.2.1.4 for Δ=DobjEobjDobj*.
20.2.2.1.4 Calculation of Matrix J
The matrix J≈Δ−1 is calculated using the following equation:
J=VΛinvV*.
Here the singular vector V of the matrix Δ are obtained using the following characteristic equation:
VΛV*=Δ.
The regularized inverse Λinv of the diagonal singular value matrix Λ is computed as
The relative regularization scalar TregΛ is determined using absolute threshold Treg and maximal value of Λ as
TregΛ=max(λi,j)Treg,Treg=10−2.
20.2.3. Decorrelation
The decorrelated signals Xd are created from the decorrelator described in 6.6.2 of ISO/IEC 23003-1:2007, with bsDecorrConfig==0 and a decorrelator index, X, according to tables in
Xd=decorrFunc(MpreYdry).
20.2.4. Mixing Matrix P
The calculation of mixing matrix P=(Pdry Pwet) is controlled by the bitstream element bsDecorrelationMethod. The matrix P has size Nout×2Nout and the Pdry and Pwet have both the size Nout×Nout.
20.2.4.1 Energy Compensation Mode
The energy compensation mode uses decorrelated signals to compensate for the loss of energy in the parametric reconstruction. The mixing matrices Pdry and Pwet are given by:
where λDec=4 is a constant used to limit the amount of decorrelated component added to the output signals.
20.2.4.2 Limited Covariance Adjustment Mode
The limited covariance adjustment mode ensures that the covariance matrix of the mixed decorrelated signals PwetYdry approximates the difference covariance matrix ΔE: PwetEYwetPwet*≈ΔE. The mixing matrices Pdry and Pwet are defined using the following equations:
Pdry=I,
Pwet=(V1√{square root over (Q1)}V1*)(V2√{square root over (Q2inv)}V2*),
where the regularized inverse Q2inv of the diagonal singular value matrix Q2 is computed as
The relative regularization scalar TregΛ is determined using absolute threshold Treg and maximal value of Q2inv as
TregΛ=max(Q2inv(i,i))Treg,Treg=10−2.
The matrix ΔE is decomposed using the Singular Value Decomposition as:
ΔE=V1Q1V1*.
The covariance matrix of the decorrelated signals EYwet is also expressed using Singular Value Decomposition:
EYwet=V2Q2V2*.
20.2.4.3. General Covariance Adjustment Mode
The general covariance adjustment mode ensures that the covariance matrix of the final output signals Ŷ (EŶ=ŶŶ*) approximates the target covariance matrix: EŶ≈C. The mixing matrix P is defined using the following equation:
P=(V1√{circumflex over (Q)}1V1*)H(V2√{square root over (Q2inv)}V2*),
where the regularized inverse Q2inv of the diagonal singular value matrix Q2 is computed as
The relative regularization scalar TregΛ is determined using absolute threshold Treg and maximal value of Q2inv as
TregΛ=max(Q2inv(i,i))Treg,Treg=10−2.
The target covariance matrix C is decomposed using the Singular Value Decomposition as:
C=V1Q1V1*.
The covariance matrix of the combined signals EYcom is also expressed using Singular Value Decomposition:
EYcom=V2Q2V2*.
The matrix H represents a prototype weighting matrix of size (Nout×2Nout) and is given by the following equation:
20.2.4.4 Introduced Covariance Matrices
The matrix ΔE represents the difference between the target output covariance matrix C and the covariance matrix EYdry of the parametrically reconstructed signals and is given by:
ΔE=C−EYdry.
The matrix EYdry represents the covariance matrix of the parametrically estimated signals EYdry≈YdryYdry* and is defined using the following equation:
EYdry=RUEU*R*.
The matrix EYdry represents the covariance matrix of the decorrelated signals EYwet≈YwetYwet* and is defined using the following equation:
EYwet=Mpost[matdiag(MpreEYdryMpre*)]Mpost*.
Considering the signal Ycom consisting of the combination of the parametric estimated and decorrelated signals:
the covariance matrix of Ycom is defined by the following equation:
Although some aspects have been described in the context of an apparatus, it is clear that these aspects also represent a description of the corresponding method, where a block or device corresponds to a method step or a feature of a method step. Analogously, aspects described in the context of a method step also represent a description of a corresponding block or item or feature of a corresponding apparatus. Some or all of the method steps may be executed by (or using) a hardware apparatus, like for example, a microprocessor, a programmable computer or an electronic circuit. In some embodiments, some one or more of the most important method steps may be executed by such an apparatus.
The inventive encoded audio signal can be stored on a digital storage medium or can be transmitted on a transmission medium such as a wireless transmission medium or a wired transmission medium such as the Internet.
Depending on certain implementation requirements, embodiments of the invention can be implemented in hardware or in software. The implementation can be performed using a digital storage medium, for example a floppy disk, a DVD, a Blu-Ray, a CD, a ROM, a PROM, an EPROM, an EEPROM or a FLASH memory, having electronically readable control signals stored thereon, which cooperate (or are capable of cooperating) with a programmable computer system such that the respective method is performed. Therefore, the digital storage medium may be computer readable.
Some embodiments according to the invention comprise a data carrier having electronically readable control signals, which are capable of cooperating with a programmable computer system, such that one of the methods described herein is performed.
Generally, embodiments of the present invention can be implemented as a computer program product with a program code, the program code being operative for performing one of the methods when the computer program product runs on a computer. The program code may for example be stored on a machine readable carrier.
Other embodiments comprise the computer program for performing one of the methods described herein, stored on a machine readable carrier.
In other words, an embodiment of the inventive method is, therefore, a computer program having a program code for performing one of the methods described herein, when the computer program runs on a computer.
A further embodiment of the inventive methods is, therefore, a data carrier (or a digital storage medium, or a computer-readable medium) comprising, recorded thereon, the computer program for performing one of the methods described herein. The data carrier, the digital storage medium or the recorded medium are typically tangible and/or non-transitionary.
A further embodiment of the inventive method is, therefore, a data stream or a sequence of signals representing the computer program for performing one of the methods described herein. The data stream or the sequence of signals may for example be configured to be transferred via a data communication connection, for example via the Internet.
A further embodiment comprises a processing means, for example a computer, or a programmable logic device, configured to or adapted to perform one of the methods described herein.
A further embodiment comprises a computer having installed thereon the computer program for performing one of the methods described herein.
A further embodiment according to the invention comprises an apparatus or a system configured to transfer (for example, electronically or optically) a computer program for performing one of the methods described herein to a receiver. The receiver may, for example, be a computer, a mobile device, a memory device or the like. The apparatus or system may, for example, comprise a file server for transferring the computer program to the receiver.
In some embodiments, a programmable logic device (for example a field programmable gate array) may be used to perform some or all of the functionalities of the methods described herein. In some embodiments, a field programmable gate array may cooperate with a microprocessor in order to perform one of the methods described herein. Generally, the methods may be performed by any hardware apparatus.
While this invention has been described in terms of several embodiments, there are alterations, permutations, and equivalents which will be apparent to others skilled in the art and which fall within the scope of this invention. It should also be noted that there are many alternative ways of implementing the methods and compositions of the present invention. It is therefore intended that the following appended claims be interpreted as including all such alterations, permutations, and equivalents as fall within the true spirit and scope of the present invention.
| Number | Date | Country | Kind |
|---|---|---|---|
| 13177374 | Jul 2013 | EP | regional |
| 13189339 | Oct 2013 | EP | regional |
This application is a divisional of U.S. patent application Ser. No. 15/004,738, filed Jan. 22, 2016, which is a continuation of International Application No. PCT/EP2014/065395, filed Jul. 17, 2014, which claims priority from European Application No. 13177374.9, filed Jul. 22, 2013, and from European Application No. 13189339.8, filed Oct. 18, 2013, which are each incorporated herein in its entirety by this reference thereto.
| Number | Name | Date | Kind |
|---|---|---|---|
| 8255228 | Hilpert et al. | Aug 2012 | B2 |
| 8588427 | Uhle et al. | Nov 2013 | B2 |
| 20070189426 | Kim et al. | Aug 2007 | A1 |
| 20070194952 | Breebaart et al. | Aug 2007 | A1 |
| 20080097750 | Seefeldt et al. | Apr 2008 | A1 |
| 20080126104 | Seefeldt et al. | May 2008 | A1 |
| 20090080666 | Uhle et al. | Mar 2009 | A1 |
| 20090194756 | Kau et al. | Aug 2009 | A1 |
| 20090240503 | Miyasaka et al. | Sep 2009 | A1 |
| 20090274308 | Oh et al. | Nov 2009 | A1 |
| 20100094631 | Engdegard | Apr 2010 | A1 |
| 20100226500 | Wang et al. | Sep 2010 | A1 |
| 20110013790 | Hilpert et al. | Jan 2011 | A1 |
| 20110022402 | Engdegard et al. | Jan 2011 | A1 |
| 20110182432 | Ishikawa | Jul 2011 | A1 |
| 20110255714 | Neusinger et al. | Oct 2011 | A1 |
| 20110264456 | Koppens et al. | Oct 2011 | A1 |
| 20120207307 | Engdegard et al. | Aug 2012 | A1 |
| 20130138446 | Hellmuth et al. | May 2013 | A1 |
| 20160005406 | Yen et al. | Jan 2016 | A1 |
| Number | Date | Country |
|---|---|---|
| 1926607 | Mar 2007 | CN |
| 101010723 | Aug 2007 | CN |
| 101061751 | Oct 2007 | CN |
| 101253810 | Aug 2008 | CN |
| 101809654 | Aug 2010 | CN |
| 101911732 | Dec 2010 | CN |
| 101933344 | Dec 2010 | CN |
| 2102856 | Sep 2009 | EP |
| 2225893 | Sep 2012 | EP |
| 2495723 | Sep 2012 | EP |
| 2008511044 | Apr 2008 | JP |
| 2010525403 | Jul 2010 | JP |
| 2012505575 | Mar 2012 | JP |
| 2007009442 | Sep 2007 | KR |
| 2439719 | Jan 2012 | RU |
| 2011100135 | Jul 2012 | RU |
| 200627380 | Aug 2006 | TW |
| 200803190 | Jan 2008 | TW |
| 200828269 | Jul 2008 | TW |
| 200915300 | Apr 2009 | TW |
| 201108204 | Mar 2011 | TW |
| 2006026452 | Mar 2006 | WO |
| 2007109338 | Sep 2007 | WO |
| 2007111568 | Oct 2007 | WO |
| 2008069593 | Jun 2008 | WO |
| 2008131903 | Nov 2008 | WO |
| 2012009851 | Jan 2012 | WO |
| 2012025282 | Mar 2012 | WO |
| 2012025283 | Mar 2012 | WO |
| 2013064957 | May 2013 | WO |
| 2014126689 | Aug 2014 | WO |
| Entry |
|---|
| ISO/IEC, “Information Technology—MPEG Audio Technologies—Part 1: MPEG Surround”, ISO/IEC FDIS 23003-1:2006(E), ISO/IEC JTC 1/SC 29/WG11, Jul. 21, 2006, 289 pages. |
| Breebaart, J et al., “MPEG Spatial Audio Coding/MPEG Surround: Overview and Current Status”, Audio Engineering Society Convention Paper presented at the 119th Convention, Oct. 7-10, 2005, pp. 1-17. |
| Herre, Jurgen et al., “MPEG Surround—The ISO/MPEG Standard for Efficient and Compatible Multichannel Audio Coding”, J. Audio Eng. Soc., vol. 56, No. 11, Nov. 2008, pp. 932-955. |
| Blauert, J. , “Spatial Hearing—The Psychophysics of Human Sound Localization”, Revised Edition, The MIT Press, London, 1997, 8 pages. |
| Engdegard, J. et al., “Spatial Audio Object Coding (SAOC)—The Upcoming MPEG Standard on Parametric Object Based Audio Coding”, 124th AES Convention, Amsterdam, 2008. |
| Faller, C. et al., “Binaural Cue Coding—Part II: Schemes and applications”, IEEE Trans. on Speech and Audio Proc., vol. 11, No. 6, Nov. 2003, pp. 520-531. |
| Faller, C. , “Parametric Joint-Coding of Audio Sources”, AES Convention Paper 6752, Presented at the 120th Convention, Paris, France, May 20-23, 2006, 12 pages. |
| Girin, L. et al., “Informed Audio Source Separation from Compressed Linear Stereo Mixtures”, AES 42nd International Conference: Semantic Audio, Ilmenau, Germany, Jul. 22-24, 2011, 10 pages. |
| Herre, J. et al., “From SAC to SAOC—Recent Developments in Parametric Coding of Spatial Audio”, Fraunhofer Institute for Integrated Circuits, Illusions in Sound, AES 22nd UK Conference 2007,, Apr. 2007, pp. 12-1 through 12-8. |
| Herre, Jurgen et al., “New Concepts in Parametric Coding of Spatial Audio: From SAC to SAOC”, IEEE International Conference on Multimedia and Expo; ISBN 978-1-4244-1016-3, Jul. 2-5, 2007, pp. 1894-1897. |
| ISO/IEC 23003-1: 2007, “Information technology—MPEG audio technologies—Part 1: MPEG Surround”, International Standard:, Feb. 15, 2007, 288 pages. |
| ISO/IEC 13818-7:2003 (E) , “Information Technology: Generic coding of moving pictures an associated audio information”, Part 7: Advanced Audio Coding (AAC), 2003, 198 pages. |
| ISO/IEC FDIS 23003-2: 2010 (E) , “Spatial Audio Object Coding”, Motion Picture Expertgroup or ISO/IEC JTC1/SC29/WG11 No. N11207, ISSN 0000-0030, XP030017704 [DA] 3 *Section 3.1.1*, Jan. 18-22, 2010, pp. 79-127. |
| ISO/IEC 23003-2: 2010, “MPEG audio technologies—Part 2: Spatial Audio Object Coding (SAOC)”, ISO/IEC JTC1/SC29/WG11 (MPEG) International Standard., Oct. 1, 2010, pp. 1-130. |
| ISO/IEC 23003-1:2006/FCD, “MPEG Surround”, Jan. 16, 2006-Jan. 20, 2006, Bangkok;, ISO/IEC JTC1/SC29/WG11; No. N7947, Jan. 16-20, 2006, pp. 1-178. |
| ISO/IEC 23003-3, “Information Technology—MPEG audio technologies—Part 3: Unified Speech and Audio Coding”, 2012, 286 pages. |
| Lang, Yue et al., “Novel Low Complexity Coherence Estimation and Synthesis Algorithms for Parametric Stereo Coding”, Huawei European Research Center, Germany. Illusonic GmbH, Switzerland., 20th European Signal Processing Conference, Bucharest, Romania, Aug. 27, 2012, pp. 2427-2431. |
| Liutkus, A. et al., “Informed source separation through spectrogram coding and data embedding”, Signal Processing Journal, Jul. 18, 2011, 30 pages. |
| Ozerov, A. et al., “Informed source separation: source coding meets source separation”, IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, Oct. 16-19, 2011, New Paltz, NY, 4 pages. |
| Parvaix, M et al., “A Watermarking-Based Method for Informed Source Separation of Audio Signals With a Single Sensor”, IEEE Transactions on Audio, Speech and Language Processing, vol. 18, No. 6, Aug. 2010, pp. 1464-1475. |
| Parvaix, M. et al., “Informed Source Separation of underdetermined instantaneous Stereo Mixtures using Source Index Embedding”, IEEE ICASSP, Mar. 2010, pp. 245-248. |
| Vilkamo, J. et al., “Optimized covariance domain framework for time-frequency processing of spatial audio”, Journal of the Audio Engineering Society, 2013, pp. 403-411. |
| Zhang, S. et al., “An informed source separation system for speech signals”, 12th Annual Conference of the International Speech Communication Association (Interspeech 2011), Aug. 2011, pp. 573-576. |
| Taiwanese Office Action dated Jan. 26, 2016, Taiwan Patent Appl. No. 103124969 (English Translation Attached), 7 pages. |
| Number | Date | Country | |
|---|---|---|---|
| 20160316307 A1 | Oct 2016 | US |
| Number | Date | Country | |
|---|---|---|---|
| Parent | 15004738 | Jan 2016 | US |
| Child | 15138176 | US |
| Number | Date | Country | |
|---|---|---|---|
| Parent | PCT/EP2014/065395 | Jul 2014 | US |
| Child | 15004738 | US |
