Abstract: A lossless audio compression scheme is adapted for use in a unified lossy and lossless audio compression scheme. In the lossless compression, the adaptation rate of an adaptive filter is varied based on transient detection, such as increasing the adaptation rate where a transient is detected. A multi-channel lossless compression uses an adaptive filter that processes samples from multiple channels in predictive coding a current sample in a current channel. The lossless compression also encodes using an adaptive filter and Golomb coding with non-power of two divisor.

Abstract: An audio encoder and decoder use architectures and techniques that improve the efficiency of quantization (e.g., weighting) and inverse quantization (e.g., inverse weighting) in audio coding and decoding. The described strategies include various techniques and tools, which can be used in combination or independently. For example, an audio encoder quantizes audio data in multiple channels, applying multiple channel-specific quantizer step modifiers, which give the encoder more control over balancing reconstruction quality between channels. The encoder also applies multiple quantization matrices and varies the resolution of the quantization matrices, which allows the encoder to use more resolution if overall quality is good and use less resolution if overall quality is poor. Finally, the encoder compresses one or more quantization matrices using temporal prediction to reduce the bitrate associated with the quantization matrices. An audio decoder performs corresponding inverse processing and decoding.

Abstract: Quantization matrices facilitate digital audio encoding and decoding. An audio encoder generates and compresses quantization matrices; an audio decoder decompresses and applies the quantization matrices. The invention includes several techniques and tools, which can be used in combination or separately. For example, the audio encoder can generate quantization matrices from critical band patterns for blocks of audio data. The encoder can compute the quantization matrices directly from the critical band patterns, which can be computed from the same audio data that is being compressed. The audio encoder/decoder can use different modes for generating/applying quantization matrices depending on the coding channel mode of multi-channel audio data. The audio encoder/decoder can use different compression/decompression modes for the quantization matrices, including a parametric compression/decompression mode.

Abstract: An audio encoder regulates quality and bitrate with a control strategy. The strategy includes several features. First, an encoder regulates quantization using quality, minimum bit count, and maximum bit count parameters. Second, an encoder regulates quantization using a noise measure that indicates reliability of a complexity measure. Third, an encoder normalizes a control parameter value according to block size for a variable-size block. Fourth, an encoder uses a bit-count control loop de-linked from a quality control loop. Fifth, an encoder addresses non-monotonicity of quality measurement as a function of quantization level when selecting a quantization level. Sixth, an encoder uses particular interpolation rules to find a quantization level in a quality or bit-count control loop. Seventh, an encoder filters a control parameter value to smooth quality. Eighth, an encoder corrects model bias by adjusting a control parameter value in view of current buffer fullness.

Abstract: An audio encoder and decoder use architectures and techniques that improve the efficiency of quantization (e.g., weighting) and inverse quantization (e.g., inverse weighting) in audio coding and decoding. The described strategies include various techniques and tools, which can be used in combination or independently. For example, an audio encoder quantizes audio data in multiple channels, applying multiple channel-specific quantizer step modifiers, which give the encoder more control over balancing reconstruction quality between channels. The encoder also applies multiple quantization matrices and varies the resolution of the quantization matrices, which allows the encoder to use more resolution if overall quality is good and use less resolution if overall quality is poor. Finally, the encoder compresses one or more quantization matrices using temporal prediction to reduce the bitrate associated with the quantization matrices. An audio decoder performs corresponding inverse processing and decoding.

Abstract: An audio encoder regulates quality and bitrate with a control strategy. The strategy includes several features. First, an encoder regulates quantization using quality, minimum bit count, and maximum bit count parameters. Second, an encoder regulates quantization using a noise measure that indicates reliability of a complexity measure. Third, an encoder normalizes a control parameter value according to block size for a variable-size block. Fourth, an encoder uses a bit-count control loop de-linked from a quality control loop. Fifth, an encoder addresses non-monotonicity of quality measurement as a function of quantization level when selecting a quantization level. Sixth, an encoder uses particular interpolation rules to find a quantization level in a quality or bit-count control loop. Seventh, an encoder filters a control parameter value to smooth quality. Eighth, an encoder corrects model bias by adjusting a control parameter value in view of current buffer fullness.

Abstract: An audio encoder regulates quality and bitrate with a control strategy. The strategy includes several features. First, an encoder regulates quantization using quality, minimum bit count, and maximum bit count parameters. Second, an encoder regulates quantization using a noise measure that indicates reliability of a complexity measure. Third, an encoder normalizes a control parameter value according to block size for a variable-size block. Fourth, an encoder uses a bit-count control loop de-linked from a quality control loop. Fifth, an encoder addresses non-monotonicity of quality measurement as a function of quantization level when selecting a quantization level. Sixth, an encoder uses particular interpolation rules to find a quantization level in a quality or bit-count control loop. Seventh, an encoder filters a control parameter value to smooth quality. Eighth, an encoder corrects model bias by adjusting a control parameter value in view of current buffer fullness.

Abstract: An audio encoder regulates quality and bitrate with a control strategy. The strategy includes several features. First, an encoder regulates quantization using quality, minimum bit count, and maximum bit count parameters. Second, an encoder regulates quantization using a noise measure that indicates reliability of a complexity measure. Third, an encoder normalizes a control parameter value according to block size for a variable-size block. Fourth, an encoder uses a bit-count control loop de-linked from a quality control loop. Fifth, an encoder addresses non-monotonicity of quality measurement as a function of quantization level when selecting a quantization level. Sixth, an encoder uses particular interpolation rules to find a quantization level in a quality or bit-count control loop. Seventh, an encoder filters a control parameter value to smooth quality. Eighth, an encoder corrects model bias by adjusting a control parameter value in view of current buffer fullness.

Abstract: Techniques and tools related to coding and decoding of audio information are described. For example, redundant coded information for decoding a current frame includes signal history information associated with only a portion of a previous frame. As another example, redundant coded information for decoding a coded unit includes parameters for a codebook stage to be used in decoding the current coded unit only if the previous coded unit is not available. As yet another example, coded audio units each include a field indicating whether the coded unit includes main encoded information representing a segment of an audio signal, and whether the coded unit includes redundant coded information for use in decoding main encoded information.

Abstract: An audio encoder regulates quality and bitrate with a control strategy. The strategy includes several features. First, an encoder regulates quantization using quality, minimum bit count, and maximum bit count parameters. Second, an encoder regulates quantization using a noise measure that indicates reliability of a complexity measure. Third, an encoder normalizes a control parameter value according to block size for a variable-size block. Fourth, an encoder uses a bit-count control loop de-linked from a quality control loop. Fifth, an encoder addresses non-monotonicity of quality measurement as a function of quantization level when selecting a quantization level. Sixth, an encoder uses particular interpolation rules to find a quantization level In a quality or bit-count control loop. Seventh, an encoder filters a control parameter value to smooth quality. Eighth, an encoder corrects model bias by adjusting a control parameter value in view of current buffer fullness.

Abstract: An audio encoder regulates quality and bitrate with a control strategy. The strategy includes several features. For example, an encoder selects a quantization level within a range of quantization levels, where the selecting accounts for non-monotonicity of quality measure as a function of quantization level within the range. The encoder then quantizes audio information by the quantization level. Or, an encoder determines first and second quality measures associated with a first and second quantization levels, respectively, then determines a third quantization level within a quantization level range based upon location of a target quality on a trajectory of quality measure as a function of quantization level. The first and second quantization levels define endpoints of the quantization level range, and the first and second quality measures define endpoints of the trajectory. The function relates logarithm of quality measure in proportion to inverse logarithm of quantization level.

Abstract: An audio encoder regulates quality and bitrate with a control strategy. The strategy includes several features. First, an encoder regulates quantization using quality, minimum bit count, and maximum bit count parameters. Second, an encoder regulates quantization using a noise measure that indicates reliability of a complexity measure. Third, an encoder normalizes a control parameter value according to block size for a variable-size block. Fourth, an encoder uses a bit-count control loop de-linked from a quality control loop. Fifth, an encoder addresses non-monotonicity of quality measurement as a function of quantization level when selecting a quantization level. Sixth, an encoder uses particular interpolation rules to find a quantization level in a quality or bit-count control loop. Seventh, an encoder filters a control parameter value to smooth quality. Eighth, an encoder corrects model bias by adjusting a control parameter value in view of current buffer fullness.

Abstract: An audio encoder implements multi-channel coding decision, band truncation, multi-channel rematrixing, and header reduction techniques to improve quality and coding efficiency. In the multi-channel coding decision technique, the audio encoder dynamically selects between joint and independent coding of a multi-channel audio signal via an open-loop decision based upon (a) energy separation between the coding channels, and (b) the disparity between excitation patterns of the separate input channels. In the band truncation technique, the audio encoder performs open-loop band truncation at a cut-off frequency based on a target perceptual quality measure. In multi-channel rematrixing technique, the audio encoder suppresses certain coefficients of a difference channel by scaling according to a scale factor, which is based on current average levels of perceptual quality, current rate control buffer fullness, coding mode, and the amount of channel separation in the source.

Abstract: An audio encoder receives multi-channel audio data comprising a group of plural source channels and performs channel extension coding, which comprises encoding a combined channel for the group and determining plural parameters for representing individual source channels of the group as modified versions of the encoded combined channel. The encoder also performs frequency extension coding. The frequency extension coding can comprise, for example, partitioning frequency bands in the multi-channel audio data into a baseband group and an extended band group, and coding audio coefficients in the extended band group based on audio coefficients in the baseband group. The encoder also can perform other kinds of transforms. An audio decoder performs corresponding decoding and/or additional processing tasks, such as a forward complex transform.

Abstract: An audio encoder encodes a combined channel (e.g., a sum channel) for a group of plural physical audio channels. The encoder determines plural parameters for representing individual physical channels of the group as modified versions of the encoded combined channel. The plural parameters comprise ratios of power in each individual channel to power in the combined channel (e.g., a ratio of the power of a right channel to the power of the combined channel, and a ratio of the power of the left channel to the power of the combined channel). The plural parameters can include a complex parameter. The combined channel and the plural parameters facilitate reconstruction at the audio decoder of source channels. An audio decoder performs a forward complex transform on the multi-channel audio data and reconstructs plural channels from the multi-channel audio data. The decoder can maintain second-order statistics for the source channels.

Abstract: An audio encoder performs frequency extension coding that comprises determining one or more shape parameters using a displacement vector that corresponds to a displacement of an even number (e.g., an even number of sub-bands between a sub-band in a baseband frequency range and a sub-band in an extended-band frequency range). The shape parameters can be determined on a per-audio-block basis. Restricting a displacement to an even number (in frequency extension coding or in other signal modulation schemes) can improve the quality of reconstructed audio. An audio encoder also can perform frequency extension coding that comprises determining one or more scale parameters at one or more audio blocks, and determining one or more anchor points for interpolating the one or more scale parameters.

Abstract: Quantization matrices facilitate digital audio encoding and decoding. An audio encoder generates and compresses quantization matrices; an audio decoder decompresses and applies the quantization matrices. The invention includes several techniques and tools, which can be used in combination or separately. For example, the audio encoder can generate quantization matrices from critical band patterns for blocks of audio data. The encoder can compute the quantization matrices directly from the critical band patterns, which can be computed from the same audio data that is being compressed. The audio encoder/decoder can use different modes for generating/applying quantization matrices depending on the coding channel mode of multi-channel audio data. The audio encoder/decoder can use different compression/decompression modes for the quantization matrices, including a parametric compression/decompression mode.

Abstract: The quality and robustness of audio echo cancellation is enhanced by selectively applying glitch recovery processes based on a quality measurement of the relative offset between capture and render audio streams. For example, large and small glitch detection is enabled for low relative offset variance; large glitch detection is enabled in a medium range of relative offset variance; and neither enabled at high variance. Further, a fast glitch recovery process suspends updating the adaptive filter coefficients of the audio echo cancellation while buffers are re-aligned to recover from the glitch, so as to avoid resetting the adaptive filter. When clock drift exists between capture and render audio streams, a multi-step compensation method is applied to improve AEC output quality in case the drifting rate is low; and a resampler is used to compensate the drift in case the drifting rate is high. An anti-clipping process detects clipping of the signals, and also suspends adaptive filter updating during clipping.

Abstract: An audio encoder implements multi-channel coding decision, band truncation, multi-channel rematrixing, and header reduction techniques to improve quality and coding efficiency. In the multi-channel coding decision technique, the audio encoder dynamically selects between joint and independent coding of a multi-channel audio signal via an open-loop decision based upon (a) energy separation between the coding channels, and (b) the disparity between excitation patterns of the separate input channels. In the band truncation technique, the audio encoder performs open-loop band truncation at a cut-off frequency based on a target perceptual quality measure. In multi-channel rematrixing technique, the audio encoder suppresses certain coefficients of a difference channel by scaling according to a scale factor, which is based on current average levels of perceptual quality, current rate control buffer fullness, coding mode, and the amount of channel separation in the source.

Abstract: An audio encoder regulates quality and bitrate with a control strategy. The strategy includes several features. First, an encoder regulates quantization using quality, minimum bit count, and maximum bit count parameters. Second, an encoder regulates quantization using a noise measure that indicates reliability of a complexity measure. Third, an encoder normalizes a control parameter value according to block size for a variable-size block. Fourth, an encoder uses a bit-count control loop de-linked from a quality control loop. Fifth, an encoder addresses non-monotonicity of quality measurement as a function of quantization level when selecting a quantization level. Sixth, an encoder uses particular interpolation rules to find a quantization level in a quality or bit-count control loop. Seventh, an encoder filters a control parameter value to smooth quality. Eighth, an encoder corrects model bias by adjusting a control parameter value in view of current buffer fullness.