An improved audio coding technique encodes audio having a low frequency transient signal, using a long block, but with a set of adapted masking thresholds. Upon identifying an audio window that contains a low frequency transient signal, masking thresholds for the long block may be calculated as usual. A set of masking thresholds calculated for the 8 short blocks corresponding to the long block are calculated. The masking thresholds for low frequency critical bands are adapted based on the thresholds calculated for the short blocks, and the resulting adapted masking thresholds are used to encode the long block of audio data. The result is encoded audio with rich harmonic content and negligible coder noise resulting from the low frequency transient signal.

Adapting masking thresholds for encoding a low frequency transient signal in audio data

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. In the header reduction technique, the audio encoder selectively modifies the quantization step size of zeroed quantization bands so as to encode in fewer frame header bits.

Quality improvement techniques in an audio encoder

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.

Bitstream syntax for multi-process audio decoding

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

Efficient coding of digital media spectral data using wide-sense perceptual similarity

In general, techniques are described by which to perform spatial masking with respect to spherical harmonic coefficients. As one example, an audio encoding device comprising a processor may perform various aspects of the techniques. The processor may be configured to perform spatial analysis based on the spherical harmonic coefficients describing a three-dimensional sound field to identify a spatial masking threshold. The processor may further be configured to render the multi-channel audio data from the plurality of spherical harmonic coefficients, and compress the multi-channel audio data based on the identified spatial masking threshold to generate a bitstream.

Performing spatial masking with respect to spherical harmonic coefficients

The embedded audio coder (EAC) is a fully scalable psychoacoustic audio coder which uses a novel perceptual audio coding approach termed “implicit auditory masking” which is intermixed with a scalable entropy coding process. When encoding and decoding an audio file using the EAC, auditory masking thresholds are not sent to a decoder. Instead, the masking thresholds are automatically derived from already coded coefficients. Furthermore, in one embodiment, rather than quantizing the audio coefficients according to the auditory masking thresholds, the masking thresholds are used to control the order that the coefficients are encoded. In particular, in this embodiment, during the scalable coding, larger audio coefficients are encoded first, as the larger components are the coefficients that contribute most to the audio energy level and lead to a higher auditory masking threshold.

System and method for embedded audio coding with implicit auditory masking

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System and method for embedded audio coding with implicit auditory masking