Patent Grant
9711156
The present disclosure is generally related to signal processing.
Advances in technology have resulted in smaller and more powerful computing devices. For example, there currently exist a variety of portable personal computing devices, including wireless computing devices, such as portable wireless telephones, personal digital assistants (PDAs), and paging devices that are small, lightweight, and easily carried by users. More specifically, portable wireless telephones, such as cellular telephones and Internet Protocol (IP) telephones, can communicate voice and data packets over wireless networks. Further, many such wireless telephones include other types of devices that are incorporated therein. For example, a wireless telephone can also include a digital still camera, a digital video camera, a digital recorder, and an audio file player.
In traditional telephone systems (e.g., public switched telephone networks (PSTNs)), signal bandwidth is limited to the frequency range of 300 Hertz (Hz) to 3.4 kiloHertz (kHz). In wideband (WB) applications, such as cellular telephony and voice over internet protocol (VoIP), signal bandwidth may span the frequency range from 50 Hz to 7 kHz. Super wideband (SWB) coding techniques support bandwidth that extends up to around 16 kHz. Extending signal bandwidth from narrowband telephony at 3.4 kHz to SWB telephony of 16 kHz may improve the quality of signal reconstruction, intelligibility, and naturalness.
SWB coding techniques typically involve encoding and transmitting the lower frequency portion of the signal (e.g., 50 Hz to 7 kHz, also called the “low-band”). For example, the low-band may be represented using filter parameters and/or a low-band excitation signal. However, in order to improve coding efficiency, the higher frequency portion of the signal (e.g., 7 kHz to 16 kHz, also called the “high-band”) may not be fully encoded and transmitted. Instead, a receiver may utilize signal modeling to predict the high-band. In some implementations, data associated with the high-band may be provided to the receiver to assist in the prediction. Such data may be referred to as “side information,” and may include gain information, line spectral frequencies (LSFs, also referred to as line spectral pairs (LSPs)), etc. High-band prediction using a signal model may be acceptably accurate when the low-band signal is sufficiently correlated to the high-band signal. However, in the presence of noise, the correlation between the low-band and the high-band may be weak, and the signal model may no longer be able to accurately represent the high-band. This may result in artifacts (e.g., distorted speech) at the receiver.
Systems and methods of performing conditional filtering of an audio signal for gain determination in an audio coding system are disclosed. The described techniques include determining whether an audio signal to be encoded for transmission includes a component (e.g., noise) that may result in audible artifacts upon reconstruction of the audio signal. For example, the underlying signal model may interpret the noise as speech data, which may result in an erroneous reconstruction of the audio signal. In accordance with the described techniques, in the presence of artifact-inducing components, conditional filtering may be performed to a high-band portion of the audio signal and the filtered high-band output may be used to generate gain information for the high-band portion. The gain information based on the filtered high-band output may lead to reduced audible artifacts upon reconstruction of the audio signal at a receiver.
In a particular embodiment, a method includes determining, based on spectral information corresponding to an audio signal that includes a low-band portion and a high-band portion, that the audio signal includes a component corresponding to an artifact-generating condition. The method also includes filtering the high-band portion of the audio signal to generate a filtered high-band output. The method further includes generating an encoded signal. Generating the encoded signal includes determining gain information based on a ratio of a first energy corresponding to the filtered high-band output to a second energy corresponding to the low-band portion to reduce an audible effect of the artifact-generating condition.
In a particular embodiment, a method includes comparing an inter-line spectral pair (LSP) spacing associated with a frame of an audio signal to at least one threshold. The method also includes conditional filtering of a high-band portion of the audio signal to generate a filtered high-band output based at least partially on the comparing. The method includes determining gain information based on a ratio of a first energy corresponding to the filtered high-band output to a second energy corresponding to a low-band portion of the audio signal.
In another particular embodiment, an apparatus includes a noise detection circuit configured to determine, based on spectral information corresponding to an audio signal that includes a low-band portion and a high-band portion, that the audio signal includes a component corresponding to an artifact-generating condition. The apparatus includes a filtering circuit responsive to the noise detection circuit and configured to filter the high-band portion of the audio signal to generate a filtered high-band output. The apparatus also includes a gain determination circuit configured to determine gain information based on a ratio of a first energy corresponding to the filtered high-band output to a second energy corresponding to the low-band portion to reduce an audible effect of the artifact-generating condition.
In another particular embodiment, an apparatus includes means for determining, based on spectral information corresponding to an audio signal that includes a low-band portion and a high-band portion, that the audio signal includes a component corresponding to an artifact-generating condition. The apparatus also includes means for filtering a high-band portion of the audio signal to generate a filtered high-band output. The apparatus includes means for generating an encoded signal. The means for generating the encoded signal includes means for determining gain information based on a ratio of a first energy corresponding to the filtered high-band output to a second energy corresponding to the low-band portion to reduce an audible effect of the artifact-generating condition.
In another particular embodiment, a non-transitory computer-readable medium includes instructions that, when executed by a computer, cause the computer to determine, based on spectral information corresponding to an audio signal that includes a low-band portion and a high-band portion, that the audio signal includes a component corresponding to an artifact-generating condition, to filter the high-band portion of the audio signal to generate a filtered high-band output, and to generate an encoded signal. Generating the encoded signal includes determining gain information based on a ratio of a first energy corresponding to the filtered high-band output to a second energy corresponding to the low-band portion to reduce an audible effect of the artifact-generating condition.
Particular advantages provided by at least one of the disclosed embodiments include an ability to detect artifact-inducing components (e.g., noise) and to selectively perform filtering in response to detecting such artifact-inducing components to affect gain information, which may result in more accurate signal reconstruction at a receiver and fewer audible artifacts. Other aspects, advantages, and features of the present disclosure will become apparent after review of the entire application, including the following sections: Brief Description of the Drawings, Detailed Description, and the Claims.
Referring to
It should be noted that in the following description, various functions performed by the system 100 of
The system 100 includes an analysis filter bank 110 that is configured to receive an input audio signal 102. For example, the input audio signal 102 may be provided by a microphone or other input device. In a particular embodiment, the input audio signal 102 may include speech. The input audio signal may be a super wideband (SWB) signal that includes data in the frequency range from approximately 50 hertz (Hz) to approximately 16 kilohertz (kHz). The analysis filter bank 110 may filter the input audio signal 102 into multiple portions based on frequency. For example, the analysis filter bank 110 may generate a low-band signal 122 and a high-band signal 124. The low-band signal 122 and the high-band signal 124 may have equal or unequal bandwidths, and may be overlapping or non-overlapping. In an alternate embodiment, the analysis filter bank 110 may generate more than two outputs.
The low-band signal 122 and the high-band signal 124 may occupy non-overlapping frequency bands. For example, the low-band signal 122 and the high-band signal 124 may occupy non-overlapping frequency bands of 50 Hz-7 kHz and 7 kHz-16 kHz. In an alternate embodiment, the low-band signal 122 and the high-band signal 124 may occupy non-overlapping frequency bands of 50 Hz-8 kHz and 8 kHz-16 kHz. In an yet another alternate embodiment, the low-band signal 122 and the high-band signal 124 may overlap (e.g., 50 Hz-8 kHz and 7 kHz-16 kHz), which may enable a low-pass filter and a high-pass filter of the analysis filter bank 110 to have a smooth rolloff, which may simplify design and reduce cost of the low-pass filter and the high-pass filter. Overlapping the low-band signal 122 and the high-band signal 124 may also enable smooth blending of low-band and high-band signals at a receiver, which may result in fewer audible artifacts.
It should be noted that although the example of
The system 100 may include a low-band analysis module 130 configured to receive the low-band signal 122. In a particular embodiment, the low-band analysis module 130 may represent an embodiment of a code excited linear prediction (CELP) encoder. The low-band analysis module 130 may include a linear prediction (LP) analysis and coding module 132, a linear prediction coefficient (LPC) to line spectral pair (LSP) transform module 134, and a quantizer 136. LSPs may also be referred to as line spectral frequencies (LSFs), and the two terms may be used interchangeably herein. The LP analysis and coding module 132 may encode a spectral envelope of the low-band signal 122 as a set of LPCs. LPCs may be generated for each frame of audio (e.g., 20 milliseconds (ms) of audio, corresponding to 320 samples at a sampling rate of 16 kHz), each sub-frame of audio (e.g., 5 ms of audio), or any combination thereof. The number of LPCs generated for each frame or sub-frame may be determined by the “order” of the LP analysis performed. In a particular embodiment, the LP analysis and coding module 132 may generate a set of eleven LPCs corresponding to a tenth-order LP analysis.
The LPC to LSP transform module 134 may transform the set of LPCs generated by the LP analysis and coding module 132 into a corresponding set of LSPs (e.g., using a one-to-one transform). Alternately, the set of LPCs may be one-to-one transformed into a corresponding set of parcor coefficients, log-area-ratio values, immittance spectral pairs (ISPs), or immittance spectral frequencies (ISFs). The transform between the set of LPCs and the set of LSPs may be reversible without error.
The quantizer 136 may quantize the set of LSPs generated by the transform module 134. For example, the quantizer 136 may include or be coupled to multiple codebooks that include multiple entries (e.g., vectors). To quantize the set of LSPs, the quantizer 136 may identify entries of codebooks that are “closest to” (e.g., based on a distortion measure such as least squares of mean square error) the set of LSPs. The quantizer 136 may output an index value or series of index values corresponding to the location of the identified entries in the codebooks. The output of the quantizer 136 may thus represent low-band filter parameters that are included in a low-band bit stream 142.
The low-band analysis module 130 may also generate a low-band excitation signal 144. For example, the low-band excitation signal 144 may be an encoded signal that is generated by quantizing a LP residual signal that is generated during the LP process performed by the low-band analysis module 130. The LP residual signal may represent prediction error.
The system 100 may further include a high-band analysis module 150 configured to receive the high-band signal 124 from the analysis filter bank 110 and the low-band excitation signal 144 from the low-band analysis module 130. The high-band analysis module 150 may generate high-band side information 172 based on one or more of the high-band signal 124, the low-band excitation signal 144, or a high-band filtered output 168, such as described in further detail with respect to
The high-band analysis module 150 may include a high-band excitation generator 160. The high-band excitation generator 160 may generate a high-band excitation signal by extending a spectrum of the low-band excitation signal 144 into the high-band frequency range (e.g., 7 kHz-16 kHz). To illustrate, the high-band excitation generator 160 may apply a transform to the low-band excitation signal (e.g., a non-linear transform such as an absolute-value or square operation) and may mix the transformed low-band excitation signal with a noise signal (e.g., white noise modulated according to an envelope corresponding to the low-band excitation signal 144) to generate the high-band excitation signal. The high-band excitation signal may be used by a high-band gain determination module 162 to determine one or more high-band gain parameters that are included in the high-band side information 172.
The high-band analysis module 150 may also include an LP analysis and coding module 152, a LPC to LSP transform module 154, and a quantizer 156. Each of the LP analysis and coding module 152, the transform module 154, and the quantizer 156 may function as described above with reference to corresponding components of the low-band analysis module 130, but at a comparatively reduced resolution (e.g., using fewer bits for each coefficient, LSP, etc.). In another example embodiment, the high band LSP Quantizer 156 may use scalar quantization where a subset of LSP coefficients are quantized individually using a pre-defined number of bits. For example, the LP analysis and coding module 152, the transform module 154, and the quantizer 156 may use the high-band signal 124 to determine high-band filter information (e.g., high-band LSPs) that are included in the high-band side information 172. In a particular embodiment, the high-band side information 172 may include high-band LSPs as well as high-band gain parameters.
The low-band bit stream 142 and the high-band side information 172 may be multiplexed by a multiplexer (MUX) 180 to generate an output bit stream 192. The output bit stream 192 may represent an encoded audio signal corresponding to the input audio signal 102. For example, the output bit stream 192 may be transmitted (e.g., over a wired, wireless, or optical channel) and/or stored. At a receiver, reverse operations may be performed by a demultiplexer (DEMUX), a low-band decoder, a high-band decoder, and a filter bank to generate an audio signal (e.g., a reconstructed version of the input audio signal 102 that is provided to a speaker or other output device). The number of bits used to represent the low-band bit stream 142 may be substantially larger than the number of bits used to represent the high-band side information 172. Thus, most of the bits in the output bit stream 192 represent low-band data. The high-band side information 172 may be used at a receiver to regenerate the high-band excitation signal from the low-band data in accordance with a signal model. For example, the signal model may represent an expected set of relationships or correlations between low-band data (e.g., the low-band signal 122) and high-band data (e.g., the high-band signal 124). Thus, different signal models may be used for different kinds of audio data (e.g., speech, music, etc.), and the particular signal model that is in use may be negotiated by a transmitter and a receiver (or defined by an industry standard) prior to communication of encoded audio data. Using the signal model, the high-band analysis module 150 at a transmitter may be able to generate the high-band side information 172 such that a corresponding high-band analysis module at a receiver is able to use the signal model to reconstruct the high-band signal 124 from the output bit stream 192.
In the presence of noise, however, high-band synthesis at the receiver may lead to noticeable artifacts, because insufficient correlation between the low-band and the high-band may cause the underlying signal model to perform sub-optimally in reliable signal reconstruction. For example, the signal model may incorrectly interpret the noise components in high band as speech, and may thus cause generation of gain parameters that attempt to replicate the noise at a receiver, leading to the noticeable artifacts. Examples of such artifact-generating conditions include, but are not limited to, high-frequency noises such as automobile horns and screeching brakes. To illustrate, a first spectrogram 210 in
To reduce such artifacts, the high-band analysis module 150 may perform a conditional high-band filtering. For example, the high-band analysis module 150 may include an artifact inducing component detection module 158 that is configured to detect artifact-inducing components, e.g., the artifact-inducing component shown in the first spectrogram 210 of
One or more tests may be performed to evaluate whether an audio signal includes an artifact-generating condition. For example, a first test may include comparing a minimum inter-LSP spacing that is detected in a set of LSPs (e.g., LSPs for a particular frame of the audio signal) to a first threshold. A small spacing between LSPs corresponds to a relatively strong signal at a relatively narrow frequency range. In a particular embodiment, when the high-band signal 124 is determined to result in a frame having a minimum inter-LSP spacing that is less than the first threshold, an artifact-generating condition is determined to be present in the audio signal and filtering may be enabled for the frame.
As another example, a second test may include comparing an average minimum inter-LSP spacing for multiple consecutive frames to a second threshold. For example, when a particular frame of an audio signal has a minimum LSP spacing that is greater than the first threshold but less than a second threshold, an artifact-generating condition may still be determined to be present if an average minimum inter-LSP spacing for multiple frames (e.g., a weighted average of the minimum inter-LSP spacing for the four most recent frames including the particular frame) is smaller than a third threshold. As a result, filtering may be enabled for the particular frame.
As another example, a third test may include determining if a particular frame follows a filtered frame of the audio signal. If the particular frame follows a filtered frame, filtering may be enabled for the particular frame based on the minimum inter-LSP spacing of the particular frame being less than the second threshold.
Three tests are described for illustrative purposes. Filtering for a frame may be enabled in response to any one or more of the tests (or combinations of the tests) being satisfied or in response to one or more other tests or conditions being satisfied. For example, a particular embodiment may include determining whether or not to enable filtering based on a single test, such as the first test described above, without applying either of the second test or the third test. Alternate embodiments may include determining whether or not to enable filtering based on the second test without applying either of the first test or the third test, or based on the third test without applying either of the first test or the second test. As another example, a particular embodiment may include determining whether or not to enable filtering based on two tests, such as the first test and the second test, without applying the third test. Alternate embodiments may include determining whether or not to enable filtering based on the first test and the third test without applying the second test, or based on the second test and the third test without applying the first test.
In a particular embodiment, the artifact inducing component detection module 158 may determine parameters from the audio signal to determine whether an audio signal includes a component that will result in audible artifacts. Examples of such parameters include a minimum inter-LSP spacing and an average minimum inter-LSP spacing. For example, a tenth order LP process may generate a set of eleven LPCs that are transformed to ten LSPs. The artifact inducing component detection module 158 may determine, for a particular frame of audio, a minimum (e.g., smallest) spacing between any two of the ten LSPs. Typically, sharp and sudden noises, such as car horns and screeching brakes, result in closely spaced LSPs (e.g., the “strong” 13 kHz noise component in the first spectrogram 210 may be closely surrounded by LSPs at 12.95 kHz and 13.05 kHz). The artifact inducing component detection module 158 may determine a minimum inter-LSP spacing and an average minimum inter-LSP spacing, as shown in the following C++-style pseudocode that may be executed by or implemented by the artifact inducing component detection module 158.
The artifact inducing component detection module 158 may further determine a weighted-average minimum inter-LSP spacing in accordance with the following pseudocode. The following pseudocode also includes resetting inter-LSP spacing in response to a mode transition. Such mode transitions may occur in devices that support multiple encoding modes for music and/or speech. For example, the device may use an algebraic CELP (ACELP) mode for speech and an audio coding mode, i.e., a generic signal coding (GSC) for music-type signals. Alternately, in certain low-rate scenarios, the device may determine based on feature parameters (e.g., tonality, pitch drift, voicing, etc.) that an ACELP/GSC/modified discrete cosine transform (MDCT) mode may be used.
After determining the minimum inter-LSP spacing and the average minimum inter-LSP spacing, the artifact inducing component detection module 158 may compare the determined values to one or more thresholds in accordance with the following pseudocode to determine whether artifact-inducing noise exists in the frame of audio. When artifact-inducing noise exists, the artifact inducing component detection module 158 may cause the filtering module 166 to perform filtering of the high-band signal 124.
In a particular embodiment, the conditional filtering module 166 may selectively perform filtering when artifact-inducing noise is detected. The filtering module 166 may filter the high-band signal 124 prior to determination of one or more gain parameters of the high-band side information 172. For example, the filtering may include finite impulse response (FIR) filtering. In a particular embodiment, the filtering may be performed using adaptive high-band LPCs 164 from the LP analysis and coding module 152 and may generate a high-band filtered output 168. The high-band filtered output 168 may be used to generate at least a portion of the high-band side information 172.
In a particular embodiment, the filtering may be performed in accordance with the filtering equation:
where ai are the high-band LPCs, L is the LPC order (e.g., 10), and γ (gamma) is a weighting parameter. In a particular embodiment, the weighting parameter γ may have a constant value. In other embodiments, the weighting parameter γ may be adaptive and may be determined based on inter-LSP spacing. For example, a value of the weighting parameter γ may be determined from the linear mapping of γ to inter-LSP spacing illustrated by the graph 300 of
The system 100 of
The high-band signal 124 (e.g., the high-band portion of the input signal 102 of
The synthesis filter 402 is used to emulate decoding of the high-band signal based on the low-band excitation signal 144 and the high-band LPCs 164. For example, the low-band excitation signal 144 may be transformed and mixed with a modulated noise signal at the high-band excitation generator 160 to generate a high-band excitation signal 440. The high-band excitation signal 440 is provided as an input to the synthesis filter 402, which is configured according to the high-band LPCs 164 to generate a synthesized high-band signal 442. Although the synthesis filter 402 is illustrated as receiving the high-band LPCs 164, in other embodiments the LSPs output by the LPC to LSP transformation module 154 may be transformed back to LPCs and provided to the synthesis filter 402. Alternatively, the output of the quantizer 156 may be un-quantized, transformed back to LPCs, and provided to the synthesis filter 402, to more accurately emulate reproduction of the LPCs that occurs at a receiving device.
While the synthesized high-band signal 442 may traditionally be compared to the high-band signal 124 to generate gain information for high-band side information, when the high-band signal 124 includes an artifact-generating component, gain information may be used to attenuate the artifact-generating component by use of a selectively filtered high-band signal 446.
To illustrate, the filtering module 166 may be configured to receive a control signal 444 from the artifact inducing component detection module 158. For example, the control signal 444 may include a value corresponding to a smallest detected inter-LSP spacing, and the filtering module 166 may selectively apply filtering based on the minimum detected inter-LSP spacing to generate a filtered high-band output as the selectively filtered high-band signal 446. As another example, the filtering module 166 may apply filtering to generate a filtered high-band output as the selectively filtered high-band signal 446 using a value of the inter-LSP spacing to determine a value of the weighting factor γ, such as according to the mapping illustrated in
The selectively and/or adaptively filtered high-band signal 446 may be compared to the synthesized high-band signal 442 and/or compared to the low band signal 122 of
The synthesized high-band signal 442 may also be provided to the temporal gain calculator 406. The temporal gain calculator 406 may determine a ratio of an energy corresponding to the synthesized high-band signal and/or an energy corresponding to the low band signal 122 of
The high-band filter parameters 450, the high-band temporal gain information 452, and the high-band frame gain information 454 may collectively correspond to the high-band side information 172 of
Referring to
The method 500 may include receiving an audio signal to be reproduced (e.g., a speech coding signal model), at 502. In a particular embodiment, the audio signal may have a bandwidth from approximately 50 Hz to approximately 16 kHz and may include speech. For example, in
The method 500 may include determining, based on spectral information corresponding to the audio signal, that the audio signal includes a component corresponding to an artifact-generating condition, at 504. The audio signal may be determined to include the component corresponding to an artifact-generating condition in response to the inter-LSP spacing being less than a first threshold, such as “THR2” in the pseudocode corresponding to
The method 500 includes filtering the audio signal, at 506. For example, the audio signal may include a low-band portion and a high-band portion, such as the low-band signal 122 and the high-band signal 124 of
As an example, an inter-line spectral pair (LSP) spacing associated with a frame of the audio signal may be determined as a smallest of a plurality of inter-LSP spacings corresponding to a plurality of LSPs generated during linear predictive coding (LPC) of the frame. The method 500 may include determining an adaptive weighting factor based on the inter-LSP spacing and performing the filtering using the adaptive weighting factor. For example, the adaptive weighting factor may be applied to high-band linear prediction coefficients, such as by applying the term (1−γ)i to the linear prediction coefficients ai as described with respect to the filter equation described with respect to
The adaptive weighting factor may be determined according to a mapping that associates inter-LSP spacing values to values of the adaptive weighting factor, such as illustrated in
The method 500 may include generating an encoded signal based on the filtering to reduce an audible effect of the artifact-generating condition, at 508. The method 500 ends, at 510.
The method 500 may be performed by the system 100 of
To illustrate, the high-band side information 172 of
In particular embodiments, the method 500 of
Referring to
An inter-line spectral pair (LSP) spacing associated with a frame of an audio signal is compared to at least one threshold, at 602, and the audio signal may be filtered based at least partially on a result of the comparing, at 604. Although comparing the inter-LSP spacing to at least one threshold may indicate the presence of an artifact-generating component in the audio signal, the comparison need not indicate, detect, or require the actual presence of an artifact-generating component. For example, one or more thresholds used in the comparison may be set to provide an increased likelihood that gain control is performed when an artifact-generating component is present in the audio signal while also providing an increased likelihood that filtering is performed without an artifact-generating component being present in the audio signal (e.g., a ‘false positive’). Thus, the method 600 may perform filtering without determining whether an artifact-generating component is present in the audio signal.
An inter-line spectral pair (LSP) spacing associated with a frame of the audio signal may be determined as a smallest of a plurality of inter-LSP spacings corresponding to a plurality of LSPs generated during linear predictive coding (LPC) of the frame. The audio signal may be filtered in response to the inter-LSP spacing being less than a first threshold. As another example, the audio signal may be filtered in response to the inter-LSP spacing being less than a second threshold and at least one of: an average inter-LSP spacing being less than a third threshold, the average inter-LSP spacing based on the inter-LSP spacing associated with the frame and at least one other inter-LSP spacing associated with at least one other frame of the audio signal, or filtering corresponding to another frame of the audio signal being enabled, the other frame preceding the frame of the audio signal.
Filtering the audio signal may include filtering the audio signal using adaptive linear prediction coefficients (LPCs) associated with a high-band portion of the audio signal to generate high-band filtered output. The filtering may be performed using an adaptive weighting factor. For example, the adaptive weighting factor may be determined based on the inter-LSP spacing, such as the adaptive weighting factor γ described with respect to
In particular embodiments, the method 600 of
Referring to
The method 700 may include determining an inter-LSP spacing associated with a frame of an audio signal, at 702. The inter-LSP spacing may be the smallest of a plurality of inter-LSP spacings corresponding to a plurality of LSPs generated during a linear predictive coding of the frame. For example, the inter-LSP spacing may be determined as illustrated with reference to the “lsp_spacing” variable in the pseudocode corresponding to
The method 700 may also include determining an average inter-LSP spacing based on the inter-LSP spacing associated with the frame and at least one other inter-LSP spacing associated with at least one other frame of the audio signal, at 704. For example, the average inter-LSP spacing may be determined as illustrated with reference to the “Average_lsp_shb_spacing” variable in the pseudocode corresponding to
The method 700 may include determining whether the inter-LSP spacing is less than a first threshold, at 706. For example, in the pseudocode of
When the inter-LSP spacing is not less than the first threshold, the method 700 may include determining whether the inter-LSP spacing is less than a second threshold, at 710. For example, in the pseudocode of
In particular embodiments, the method 700 of
Referring to
The CODEC 834 may include a filtering system 874. In a particular embodiment, the filtering system 874 may include one or more components of the system 100 of
In a particular embodiment, the processor 810, the display controller 826, the memory 832, the CODEC 834, and the wireless controller 840 are included in a system-in-package or system-on-chip device (e.g., a mobile station modem (MSM)) 822. In a particular embodiment, an input device 830, such as a touchscreen and/or keypad, and a power supply 844 are coupled to the system-on-chip device 822. Moreover, in a particular embodiment, as illustrated in
In conjunction with the described embodiments, an apparatus is disclosed that includes means for means for determining, based on spectral information corresponding to an audio signal, that the audio signal includes a component corresponding to an artifact-generating condition. For example, the means for determining may include the artifact inducing component detection module 158 of
The apparatus may also include means for filtering the audio signal responsive to the means for determining. For example, the means for filtering may include the filtering module 168 of
The apparatus may also include means for generating an encoded signal based on the filtered audio signal to reduce an audible effect of the artifact-generating condition. For example, the means for generating may include the high-band analysis module 150 of
Those of skill would further appreciate that the various illustrative logical blocks, configurations, modules, circuits, and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software executed by a processing device such as a hardware processor, or combinations of both. Various illustrative components, blocks, configurations, modules, circuits, and steps have been described above generally in terms of their functionality. Whether such functionality is implemented as hardware or executable software depends upon the particular application and design constraints imposed on the overall system. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present disclosure.
The steps of a method or algorithm described in connection with the embodiments disclosed herein may be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. A software module may reside in a memory device, such as random access memory (RAM), magnetoresistive random access memory (MRAM), spin-torque transfer MRAM (STT-MRAM), flash memory, read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), registers, hard disk, a removable disk, or a compact disc read-only memory (CD-ROM). An exemplary memory device is coupled to the processor such that the processor can read information from, and write information to, the memory device. In the alternative, the memory device may be integral to the processor. The processor and the storage medium may reside in an application-specific integrated circuit (ASIC). The ASIC may reside in a computing device or a user terminal. In the alternative, the processor and the storage medium may reside as discrete components in a computing device or a user terminal.
The previous description of the disclosed embodiments is provided to enable a person skilled in the art to make or use the disclosed embodiments. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the principles defined herein may be applied to other embodiments without departing from the scope of the disclosure. Thus, the present disclosure is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope possible consistent with the principles and novel features as defined by the following claims.
The present application claims priority from commonly owned U.S. Provisional Patent Application No. 61/762,807 filed on Feb. 8, 2013, the content of which is expressly incorporated herein by reference in its entirety.
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