Abstract: A transcoder reduces excess requantization error in quantization of spectral data. The transcoder phase shifts data decompressed by a decompressor. The phase shifting causes a change to corresponding spectral data produced in later transform coding of the decompressed data. When the spectral data is then quantized to reduce bitrate, the earlier phase shifting reduces excess requantization error. After transcoding, a second decompressor can compensate for the phase shifting by, for example, reverse shifting by the amount of the phase shift. Instead of phase shifting, the transcoder can reduce excess requantization error by, for example, adding random noise to the decompressed data or changing transform block sizes.

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: A gain-constrained noise suppression for speech more precisely estimates noise, including during speech, to reduce musical noise artifacts introduced from noise suppression. The noise suppression operates by applying a spectral gain G(m, k) to each short-time spectrum value S(m, k) of a speech signal, where m is the frame number and k is the spectrum index. The spectrum values are grouped into frequency bins, and a noise characteristic estimated for each bin classified as a “noise bin.” An energy parameter is smoothed in both the time domain and the frequency domain to improve noise estimation per bin. The gain factors G(m, k) are calculated based on the current signal spectrum and the noise estimation, then smoothed before being applied to the signal spectral values S(m, k).

Abstract: Fast headphone virtualization techniques reduces the computational expense of providing multi-channel audio virtualization (which may also include reflection and reverberation effects) on headphones. First, the number of inverse Fast Fourier Transforms (FFT) involved in an FFT-based FIR filter headphone virtualization approach is reduced by summing the contributions of N-channels in the frequency domain prior to the inverse FFT. Second, the reverberation part of a room filter is implemented as a hybrid FIR/IIR filter, where subsequent filter segments are approximated by successively scaling the result of an initial reverberation filter segment. Third, a low pass filter is added in the hybrid FIR/IIR filter to provide warmth control.

Abstract: A transcoder reduces excess requantization error in quantization of spectral data. The transcoder phase shifts data decompressed by a decompressor. The phase shifting causes a change to corresponding spectral data produced in later transform coding of the decompressed data. When the spectral data is then quantized to reduce bitrate, the earlier phase shifting reduces excess requantization error. After transcoding, a second decompressor can compensate for the phase shifting by, for example, reverse shifting by the amount of the phase shift. Instead of phase shifting, the transcoder can reduce excess requantization error by, for example, adding random noise to the decompressed data or changing transform block sizes.

Abstract: Described techniques and tools include techniques and tools for mapping digital media data (e.g., audio, video, still images, and/or text, among others) in a given format to a transport or file container format useful for encoding the data on optical disks such as digital video disks (DVDs). A digital media universal elementary stream can be used to map digital media streams (e.g., an audio stream, video stream or an image) into any arbitrary transport or file container, including optical disk formats, and other transports, such as broadcast streams, wireless transmissions, etc. The information to decode any given frame of the digital media in the stream can be carried in each coded frame. A digital media universal elementary stream includes stream components called chunks. An implementation of a digital media universal elementary stream arranges data for a media stream in frames, the frames having one or more chunks.

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: 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: 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 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: 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: 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: 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 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: 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.