Abstract: Techniques and tools for prediction of spectral coefficients in encoding and decoding are described herein. For certain types and patterns of content, coefficient prediction exploits correlation between adjacent spectral coefficients, making subsequent entropy encoding more efficient. For example, an audio encoder predictively codes quantized spectral coefficients in the quantized domain and entropy encodes results of the predictive coding. Or, for a particular quantized spectral coefficient, an audio decoder entropy decodes a difference value, computes a predictor in the quantized domain, and combines the predictor and the difference value.

Abstract: A compressed digital audio signal is transmitted from an audio source along a connection wire to an audio receiver. The digital audio signal can encode digital audio data having different sampling frequencies, frames sizes, and other information. The audio receiver that receives the digital audio signal can decode and convert the compressed digital audio signal into multiple synchronized analog signals, which are used to drive multiple speakers. The audio receiver may also synchronize the audio data with associated video data so that the audio playback and video playback are “in sync”, despite delay introduced by the audio signal decoding at the audio receiver.

Abstract: Various strategies for rate/quality control and loss resiliency in an audio codec are described. The various strategies can be used in combination or independently. For example, a real-time speech codec uses intra frame coding/decoding, adaptive multi-mode forward error correction [“FEC”], and rate/quality control techniques. Intra frames help a decoder recover quickly from packet losses, while compression efficiency is still emphasized with predicted frames. Various strategies for inserting intra frames and signaling intra/predicted frames are described. With the adaptive multi-mode FEC, an encoder adaptively selects between multiple modes to efficiently and quickly provide a level of FEC that takes into account the bandwidth currently available for FEC. The FEC information itself may be predictively encoded and decoded relative to primary encoded information. Various rate/quality and FEC control strategies allow additional adaptation to available bandwidth and network conditions.

Abstract: An encoder uses multi-pass VBR control strategies to provide constant or relatively constant quality for VBR output while guaranteeing (within tolerance) either compressed file size or, equivalently, overall average bitrate. The control strategies include various techniques and tools, which can be used in combination or independently. For example, in a first pass, an audio encoder encodes a sequence of audio data partitioned into variable-size chunks. In a second pass, the encoder encodes the sequence according to control parameters to produce output of relatively constant quality. The encoder sets checkpoints in the second pass to adjust the control parameters and/or subsequent checkpoints. The encoder selectively considers a peak bitrate constraint to limit peak bitrate. The encoder stores auxiliary information from the first pass for use in the second pass, which increases the speed of the second pass. Finally, the encoder compares signatures for the input data to check consistency between passes.

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: Frequency segmentation is important to the quality of encoding spectral data. Segmentation involves breaking the spectral data into units called sub-bands or vectors. Homogeneous segmentation may be suboptimal. Various features are described for providing spectral data intensity dependent segmentation. Finer segmentation is provided for regions of greater spectral variance and coarser segmentation is provided for more homogeneous regions. Sub-bands which have similar characteristics may be merged with very little effect on quality, whereas sub-bands with highly variable data may be better represented if a sub-band is split. Various methods are described for measuring tonality, energy, or shape of a sub-band. These various measurements are discussed in light of making decisions of when to split or merge sub-bands to provide variable frequency segmentation.

Abstract: Techniques and tools related to delayed or lost coded audio information are described. For example, a concealment technique for one or more missing frames is selected based on one or more factors that include a classification of each of one or more available frames near the one or more missing frames. As another example, information from a concealment signal is used to produce substitute information that is relied on in decoding a subsequent frame. As yet another example, a data structure having nodes corresponding to received packet delays is used to determine a desired decoder packet delay value.

Abstract: Techniques and tools for selectively using multiple entropy models in adaptive coding and decoding are described herein. For example, for multiple symbols, an audio encoder selects an entropy model from a first model set that includes multiple entropy models. Each of the multiple entropy models includes a model switch point for switching to a second model set that includes one or more entropy models. The encoder processes the multiple symbols using the selected entropy model and outputs results. Techniques and tools for generating entropy models are also described.

Abstract: Techniques and tools related to delayed or lost coded audio information are described. For example, a concealment technique for one or more missing frames is selected based on one or more factors that include a classification of each of one or more available frames near the one or more missing frames. As another example, information from a concealment signal is used to produce substitute information that is relied on in decoding a subsequent frame. As yet another example, a data structure having nodes corresponding to received packet delays is used to determine a desired decoder packet delay value.

Abstract: A mixed lossless audio compression has application to a unified lossy and lossless audio compression scheme that combines lossy and lossless audio compression within a same audio signal. The mixed lossless compression codes a transition frame between lossy and lossless coding frames to produce seamless transitions. The mixed lossless coding performs a lapped transform and inverse lapped transform to produce an appropriately windowed and folded pseudo-time domain frame, which can then be losslessly coded. The mixed lossless coding also can be applied for frames that exhibit poor lossy compression performance.

Abstract: Coding of spectral data by representing certain portions of the spectral data as a scaled version of a code-vector, where the code-vector is chosen from either a fixed predetermined codebook or a codebook taken from a baseband. Various optional features are described for modifying the code-vectors in the codebook according to some rules which allow the code-vector to better represent the data they are modeling. The code-vector modification comprises a linear or non-linear transform of one or more code-vectors, such as, by exponentiation, negation, reversing, or combining elements from plural code-vectors.

Abstract: An audio processing tool measures the quality of reconstructed audio data. For example, an audio encoder measures the quality of a block of reconstructed frequency coefficient data in a quantization loop. The invention includes several techniques and tools, which can be used in combination or separately. First, before measuring quality, the tool normalizes the block to account for variation in block sizes. Second, for the quality measurement, the tool processes the reconstructed data by critical bands, which can differ from the quantization bands used to compress the data. Third, the tool accounts for the masking effect of the reconstructed data, not just the masking effect of the original data. Fourth, the tool band weights the quality measurement, which can be used to account for noise substitution or band truncation. Finally, the tool changes quality measurement techniques depending on the channel coding mode.

Abstract: An audio processing tool measures the quality of reconstructed audio data. For example, an audio encoder measures the quality of a block of reconstructed frequency coefficient data in a quantization loop. The invention includes several techniques and tools, which can be used in combination or separately. First, before measuring quality, the tool normalizes the block to account for variation in block sizes. Second, for the quality measurement, the tool processes the reconstructed data by critical bands, which can differ from the quantization bands used to compress the data. Third, the tool accounts for the masking effect of the reconstructed data, not just the masking effect of the original data. Fourth, the tool band weights the quality measurement, which can be used to account for noise substitution or band truncation. Finally, the tool changes quality measurement techniques depending on the channel coding mode.

Abstract: A transform coder is described that performs a time-split transform in addition to a discrete cosine type transform. A time-split transform is selectively performed based on characteristics of media data. Transient detection identifies a changing signal characteristic, such as a transient in media data. After encoding an input signal from a time domain to a transform domain, a time-splitting transformer selectively perform an orthogonal sum-difference transform on adjacent coefficients indicated by a changing signal characteristic location. The orthogonal sum-difference transform on adjacent coefficients results in transforming a vector of coefficients in the transform domain as if they were multiplied by an identity matrix including at least one 2×2 time-split block along a diagonal of the matrix. A decoder performs an inverse of the described transforms.

Abstract: Techniques and tools for representing, coding, and decoding scale factor information are described herein. For example, during encoding of scale factors, an encoder uses one or more of flexible scale factor resolution selection, spatial prediction of scale factors, flexible prediction of scale factors, smoothing of noisy scale factor amplitudes, reordering of scale factor prediction residuals, and prediction of scale factor prediction residuals. Or, during decoding, a decoder uses one or more of flexible scale factor resolution selection, spatial prediction of scale factors, flexible prediction of scale factors, reordering of scale factor prediction residuals, and prediction of scale factor prediction residuals.

Abstract: A mixed lossless audio compression has application to a unified lossy and lossless audio compression scheme that combines lossy and lossless audio compression within a same audio signal. The mixed lossless compression codes a transition frame between lossy and lossless coding frames to produce seamless transitions. The mixed lossless coding performs a lapped transform and inverse lapped transform to produce an appropriately windowed and folded pseudo-time domain frame, which can then be losslessly coded. The mixed lossless coding also can be applied for frames that exhibit poor lossy compression performance.

Abstract: An audio encoder encodes side information into a compressed audio bitstream containing encoding parameters used by the encoder for one or more encoding techniques, such as a noise-mask-ratio curve used for rate control. A transcoder uses the encoder generated side information to transcode the audio from the original compressed bitstream having an initial bit-rate into a second bitstream having a new bit-rate. Because the side information is derived from the original audio, the transcoder is able to better maintain audio quality of the transcoding. The side information also allows the transcoder to re-encode from an intermediate decoding/encoding stage for faster and lower complexity transcoding.

Abstract: Traditional audio encoders may conserve coding bit-rate by encoding fewer than all spectral coefficients, which can produce a blurry low-pass sound in the reconstruction. An audio encoder using wide-sense perceptual similarity improves the quality by encoding a perceptually similar version of the omitted spectral coefficients, represented as a scaled version of already coded spectrum. The omitted spectral coefficients are divided into a number of sub-bands. The sub-bands are encoded as two parameters: a scale factor, which may represent the energy in the band; and a shape parameter, which may represent a shape of the band. The shape parameter may be in the form of a motion vector pointing to a portion of the already coded spectrum, an index to a spectral shape in a fixed code-book, or a random noise vector. The encoding thus efficiently represents a scaled version of a similarly shaped portion of spectrum to be copied at decoding.

Abstract: An audio encoder and decoder use architectures and techniques that improve the efficiency of multi-channel 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 performs a pre-processing multi-channel transform on multi-channel audio data, varying the transform so as to control quality. The encoder groups multiple windows from different channels into one or more tiles and outputs tile configuration information, which allows the encoder to isolate transients that appear in a particular channel with small windows, but use large windows in other channels. Using a variety of techniques, the encoder performs flexible multi-channel transforms that effectively take advantage of inter-channel correlation. An audio decoder performs corresponding processing and decoding. In addition, the decoder performs a post-processing multi-channel transform for any of multiple different purposes.

Abstract: An audio decoder provides a combination of decoding components including components implementing base band decoding, spectral peak decoding, frequency extension decoding and channel extension decoding techniques. The audio decoder decodes a compressed bitstream structured by a bitstream syntax scheme to permit the various decoding components to extract the appropriate parameters for their respective decoding technique.