Many types of systems use audio signal processing to create audio signals or to reproduce sound from such signals. Typically, signal processing converts audio signals to digital data and encodes the data for transmission over a network. Then, signal processing decodes the data and converts it back to analog signals for reproduction as acoustic waves.
Various ways exits for encoding or decoding audio signals. (A processor or a processing module that encodes and decodes a signal is generally referred to as a codec.) For example, audio processing for audio and video conferencing uses audio codecs to compress high-fidelity audio input so that a resulting signal for transmission retains the best quality but requires the least number of bits. In this way, conferencing equipment having the audio codec needs less storage capacity, and the communication channel used by the equipment to transmit the audio signal requires less bandwidth.
ITU-T (International Telecommunication Union Telecommunication Standardization Sector) Recommendation G.722 (1988), entitled “7 kHz audio-coding within 64 kbit/s,” which is hereby incorporated by reference, describes a method of 7 kHz audio-coding within 64 kbit/s. ISDN lines have the capacity to transmit data at 64 kbit/s. This method essentially increases the bandwidth of audio through a telephone network using an ISDN line from 3 kHz to 7 kHz. The perceived audio quality is improved. Although this method makes high quality audio available through the existing telephone network, it typically requires ISDN service from a telephone company, which is more expensive than a regular narrow band telephone service.
A more recent method that is recommended for use in telecommunications is the ITU-T Recommendation G.722.1 (2005), entitled “Low-complexity coding at 24 and 32 kbit/s for hands-free operation in system with low frame loss,” which is hereby incorporated herein by reference. This Recommendation describes a digital wideband coder algorithm that provides an audio bandwidth of 50 Hz to 7 kHz, operating at a bit rate of 24 kbit/s or 32 kbit/s, much lower than the G.722. At this data rate, a telephone having a regular modem using the regular analog phone line can transmit wideband audio signals. Thus, most existing telephone networks can support wideband conversation, as long as the telephone sets at the two ends can perform the encoding/decoding as described in G.722.1.
Some commonly used audio codecs use transform coding techniques to encode and decode audio data transmitted over a network. For example, ITU-T Recommendation G.719 (Polycom® Siren™22) as well as G.722.1.C (Polycom® Siren14™), both of which are incorporated herein by reference, use the well-known Modulated Lapped Transform (MLT) coding to compress the audio for transmission. As is known, the Modulated Lapped Transform (MLT) is a form of a cosine modulated filter bank used for transform coding of various types of signals.
In general, a lapped transform takes an audio block of length L and transforms that block into M coefficients, with the condition that L>M. For this to work, there must be an overlap between consecutive blocks of L−M samples so that a synthesized signal can be obtained using consecutive blocks of transformed coefficients.
For a Modulated Lapped Transform (MLT), the length L of the audio block is equal to the number M of coefficients so the overlap is M. Thus, the MLT basis function for the direct (analysis) transform is given by:
Similarly, the MLT basis function for the inverse (synthesis) transform is given by:
In these equations, M is the block size, the frequency index k varies from 0 to M−1, and the time index n varies from 0 to 2M−1. Lastly,
are the perfect reconstruction windows used.
MLT coefficients are determined from these basis functions as follows. The direct transform matrix Pa is the one whose entry in the n-th row and k-th column is pa(n,k). Similarly, the inverse transform matrix Ps is the one with entries ps(n,k). For a block x of 2M input samples of an input signal x(n), its corresponding vector {right arrow over (X)} of transform coefficients is computed by {right arrow over (X)}=PaTx. In turn, for a vector {right arrow over (Y)} of processed transform coefficients, the reconstructed 2M sample vector y is given by y=PS{right arrow over (Y)}. Finally, the reconstructed y vectors are superimposed on one another with M-sample overlap to generate the reconstructed signal y(n) for output.
A microphone 12 at the transmitter 10A captures source audio, and electronics sample source audio into audio blocks 14 typically spanning 20-milliseconds. At this point, the transform of the audio codec 16 converts the audio blocks 14 to sets of frequency domain transform coefficients. Each transform coefficient has a magnitude and may be positive or negative. Using techniques known in the art, these coefficients are then quantized 18, encoded, and sent to the receiver via a network 20, such as the Internet.
At the receiver 10B, a reverse process decodes and de-quantizes 19 the encoded coefficients. Finally, the audio codec 16 at the receiver 10B performs an inverse transform on the coefficients to convert them back into the time domain to produce output audio block 14 for eventual playback at the receiver's loudspeaker 13.
Audio packet loss is a common problem in videoconferencing and audio conferencing over the networks such as the Internet. As is known, audio packets represent small segments of audio. When the transmitter 10A sends packets of the transform coefficients over the Internet 20 to the receiver 10B, some packets may become lost during transmission. Once output audio is generated, the lost packets would create gaps of silence in what is output by the loudspeaker 13. Therefore, the receiver 10B preferably fills such gaps with some form of audio that has been synthesized from those packets already received from the transmitter 10A.
As shown in
As a result, what is needed is a technique for dealing with lost audio packets when conferencing over the Internet in a way that produces better audio quality and avoids buzzing and robotic artifacts.
Audio processing techniques disclosed herein can be used for audio or video conferencing. In the processing techniques, a terminal receives audio packets having transform coefficients for reconstructing an audio signal that has undergone transform coding. When receiving the packets, the terminal determines whether there are any missing packets and interpolates transform coefficients from the preceding and following good frames for insertion as coefficients for the missing packets. To interpolate the missing coefficients, for example, the terminal weighs first coefficients from the preceding good frame with a first weighting, weighs second coefficients from the following good frame with a second weighting, and sums these weighted coefficients together for insertion into the missing packets. The weightings can be based on the audio frequency and/or the number of missing packets involved. From this interpolation, the terminal produces an output audio signal by inverse transforming the coefficients.
The foregoing summary is not intended to summarize each potential embodiment or every aspect of the present disclosure.
During operation, a microphone 102 at the transmitter 100A captures source audio, and electronics sample blocks or frames of that typically spans 20-milliseconds. (Discussion concurrently refers to the flow chart in
Using techniques known in the art, these transform coefficients are then quantized with a quantizer 120 and encoded (Block 308), and the transmitter 100A sends the encoded transform coefficients in packets to the receiver 100B via a network 125, such as an IP (Internet Protocol) network, PSTN (Public Switched Telephone Network), ISDN (Integrated Services Digital Network), or the like (Block 310). The packets can use any suitable protocols or standards. For example, audio data may follow a table of contents, and all octets comprising an audio frame can be appended to the payload as a unit. For example, details of the audio frames are specified in ITU-T Recommendations G.719 and G.722.1C, which have been incorporated herein.
At the receiver 100B, an interface 120 receives the packets (Block 312). When sending the packets, the transmitter 100A creates a sequence number that is included in each packet sent. As is known, packets may pass through different routes over the network 125 from the transmitter 100A to the receiver 100B, and the packets may arrive at varying times at the receiver 100B. Therefore, the order in which the packets arrive may be random.
To handle this varying time of arrival, called “jitter,” the receiver 100B has a jitter buffer 130 coupled to the receiver's interface 120. Typically, the jitter buffer 130 holds four or more packets at a time. Accordingly, the receiver 100B reorders the packets in the jitter buffer 130 based on their sequence numbers (Block 314).
Although the packets may arrive out-of-order at the receiver 100B, the lost packet handler 140 properly re-orders the packets in the jitter buffer 130 and detects any lost (missing) packets based on the sequence. A lost packet is declared when there are gaps in the sequence numbers of the packets in the jitter buffer 130. For example, if the handler 140 discovers sequence numbers 005, 006, 007, 011 in the jitter buffer 130, then the handler 140 can declare the packets 008, 009, 010 as lost. In reality, these packets may not actually be lost and may only be late in their arrival. Yet, due to latency and buffer length restrictions, the receiver 100B discards any packets that arrive late beyond some threshold.
In a reverse process that follows, the receiver 100B decodes and de-quantizes the encoded transform coefficients (Block 316). If the handler 140 has detected lost packets (Decision 318), the lost packet handler 140 knows what good packets preceded and followed the gap of lost packets. Using this knowledge, the transform synthesizer 150 derives or interpolates the missing transform coefficients of the lost packets so the new transform coefficients can be substituted in place of the missing coefficients from the lost packets (Block 320). (In the present example, the audio codec uses MLT coding so that the transform coefficients may be referred to herein as MLT coefficients.) At this stage, the audio codec 110 at the receiver 100B performs an inverse transform on the coefficients and convert them back into the time domain to produce output audio for the receiver's loudspeaker (Blocks 322-324).
As can be seen in the above process, rather than detect lost packets and continually repeat the previous segment of received audio to fill the gap, the lost packet handler 140 handles lost packets for the transform-based codec 110 as a lost set of transform coefficients. The transform synthesizer 150 then replaces the lost set of transform coefficients from the lost packets with synthesized transform coefficients derived from neighboring packets. Then, a full audio signal without audio gaps from lost packets can be produced and output at the receiver 100B using an inverse transform of the coefficients.
In a transmission path, analog input signals picked up by the microphone 102 are converted into digital signals by converter electronics 164, and the audio codec 110 operating on the terminal's processor 160 has an encoder 200 that encodes the digital audio signals for transmission via a transmitter interface 122 over the network 125, such as the Internet. If present, a video codec having a video encoder 170 can perform similar functions for video signals.
In a receive path, the terminal 100 has a network receiver interface 124 coupled to the audio codec 110. A decoder 250 decodes the received signal, and converter electronics 164 convert the digital signals to analog signals for output to the loudspeaker 104. If present, a video codec having a video decoder 172 can perform similar functions for video signals.
An encoder 200 for a transform coding codec (e.g., a Siren codec) is illustrated in
A decoder 250 for the transform coding codec (e.g., Siren codec) is illustrated in
At this point, the transform synthesizer 258 can interpolate coefficients for missing packets. Finally, an inverse transform 260 operates as a reverse DCT and converts the signal from the frequency domain back into the time domain for transmission as an output signal 262. As can be seen, the transform synthesizer 258 helps to fill in any gaps that may result from the missing packets. Yet, all of the existing functions and algorithms of the decoder 200 remain the same.
With an understanding of the terminal 100 and the audio codec 110 provided above, discussion now turns to how the audio codec 100 interpolates transform coefficients for missing packets by using good coefficients from neighboring frames, blocks, or sets of packets received over the network. (The discussion that follows is presented in terms of MLT coefficients, but the disclosed interpolation process may apply equally well to other transform coefficients for other forms of transform coding).
As diagrammatically shown in
In general, a given packet that is lost may have one or more frames (e.g., 20-ms) of audio, may encompass only a portion of a frame, can have one or more frames for one or more channels of audio, can have one or more frames at one or more different bit rates, and can other complexities known to those skilled in the art and associated with the particular transform coding algorithm and payload format used. However, the interpolation rule 500 used to interpolate the missing transform coefficients for the missing packets can be adapted to the particular transform coding and payload formats in a given implementation.
As shown, the transform coefficients (shown here as MLT coefficients) of the preceding good frame or set 510 are called MLTA(i), and the MLT coefficients of the following good frame or set 530 are called MLTB(i). If the audio codec uses Siren™22, the index (i) ranges from 0 to 959. The general interpolation rule 520 for the absolute value the interpolated MLT coefficients 540 for the missing packets is determined based on weights 512/532 applied to the preceding and following MLT coefficients 510/230 as follows:
|MLTInterpolated(i)|=WeightA*|MLTA(i)|+WeightB*|MLTB(i)|
In the general interpolation rule, the sign 522 for the interpolated MLT coefficients, MLTInterpolated(i), 540 of the missing frame or set is randomly set as either positive or negative with equal probability. This randomness may help the audio resulting from these reconstructed packets sound more natural and less robotic.
After interpolating the MLT coefficients 540 in this way, the transform synthesizer (150;
As the number of missing packets varies, the interpolation rule 500 applies different weights 512/532 to the preceding and following MLT coefficients 510/530 to determine the interpolated MLT coefficients 540. Below are particular rules for determining the two weight factors, WeightA and WeightB, based on the number of missing packets and other parameters.
1. Single Lost Packet
As diagramed in
2. Two Lost Packets
As diagramed in
If each packet encompasses one frame of audio (e.g., 20-ms), then each set 610A-B and 622 of
3. Three to Six Lost Packets
As diagramed in
The arrangement of the packets and the frames or sets in the diagrams of
To define weight factors for interpolating missing transform coefficients, the parameters described above use frequency levels, the number of packets missing in a frame, and the location of a missing packet in a given set of missing packets. The weight factors may be defined using any one or combination of these interpolation parameters. The weight factors (WeightA, WeightB), frequency threshold, and interpolation parameters disclosed above for interpolating transform coefficients are illustrative. These weight factors, thresholds, and parameters are believed to produce the best subjective quality of audio when filling in gaps from missing packets during a conference. Yet, these factors, thresholds, and parameters may differ for a particular implementation, may be expanded beyond what is illustratively presented, and may depend on the types of equipment used, the types of audio involved (i.e., music, voice, etc.), the type of transform coding applied, and other considerations.
In any event, when concealing lost audio packets for transform-based audio codecs, the disclosed audio processing techniques produce better quality sound than the prior art solutions. In particular, even if 25% of packets are lost, the disclosed technique may still produce audio that is more intellible than current techniques. Audio packet loss occurs often in videoconferencing applications, so improving quality during such conditions is important to improving the overall videoconferencing experience. Yet, it is important that steps taken to conceal packet loss not require too much processing or storage resources at the terminal operating to conceal the loss. By applying weightings to transform coefficients in preceding and following good frames, the disclosed techniques can reduce the processing and storage resources needed.
Although described in terms of audio or video conferencing, the teachings of the present disclosure may be useful in other fields involving streaming media, including streaming music and speech. Therefore, the teachings of the present disclosure can be applied to other audio processing devices in addition to an audio conferencing endpoint and a videoconferencing endpoint, including an audio playback device, a personal music player, a computer, a server, a telecommunications device, a cellular telephone, a personal digital assistant, etc. For example, special purpose audio or videoconferencing endpoints may benefit from the disclosed techniques. Likewise, computers or other devices may be used in desktop conferencing or for transmission and receipt of digital audio, and these devices may also benefit from the disclosed techniques.
The techniques of the present disclosure can be implemented in electronic circuitry, computer hardware, firmware, software, or in any combinations of these. For example, the disclosed techniques can be implemented as instruction stored on a program storage device for causing a programmable control device to perform the disclosed techniques. Program storage devices suitable for tangibly embodying program instructions and data include all forms of non-volatile memory, including by way of example semiconductor memory devices, such as EPROM, EEPROM, and flash memory devices; magnetic disks such as internal hard disks and removable disks; magneto-optical disks; and CD-ROM disks. Any of the foregoing can be supplemented by, or incorporated in, ASICs (application-specific integrated circuits).
The foregoing description of preferred and other embodiments is not intended to limit or restrict the scope or applicability of the inventive concepts conceived of by the Applicants. In exchange for disclosing the inventive concepts contained herein, the Applicants desire all patent rights afforded by the appended claims. Therefore, it is intended that the appended claims include all modifications and alterations to the full extent that they come within the scope of the following claims or the equivalents thereof.
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