Abstract: An audio signal encoding method is provided comprising: receiving first and second audio signal frames; processing a second portion of the first audio signal frame and a first portion of the second audio signal frame using an orthogonal transformation to determine in part a first intermediate encoding result; and processing the first intermediate encoding result using an orthogonal transformation to determine a set of spectral coefficients that corresponds to at least a portion of the first audio signal frame.

Abstract: An audio signal encoding method is provided comprising: receiving first and second audio signal frames; processing a second portion of the first audio signal frame and a first portion of the second audio signal frame using an orthogonal transformation to determine in part a first intermediate encoding result; and processing the first intermediate encoding result using an orthogonal transformation to determine a set of spectral coefficients that corresponds to at least a portion of the first audio signal frame.

Abstract: A method of encoding an audio signal is provided comprising: applying multiple different time-frequency transformations to an audio signal frame; computing measures of coding efficiency across multiple frequency bands for multiple time-frequency resolutions; selecting a combination of time-frequency resolutions to represent the frame at each of the multiple frequency bands based at least in part upon the computed measures of coding efficiency; determining a window size and a corresponding transform size; determining a modification transformation; windowing the frame using the determined window size; transforming the windowed frame using the determined transform size; modifying a time-frequency resolution within a frequency band of the transform of the windowed frame using the determined modification transformation.

Abstract: A method comprises receiving input audio and target audio having a target audio characteristic. The method includes estimating key parameters that represent the target audio characteristic based on one or more of the target audio and the input audio. The method further comprises configuring a neural network, trained to be configured by the key parameters, with the key parameters to cause the neural network to perform a signal transformation of the input audio, to produce output audio having an output audio characteristic corresponding to and that matches the target audio characteristic.

Abstract: A method comprise: receiving input audio and target audio having a target audio characteristic; using a first neural network, trained to generate key parameters that represent the target audio characteristic based on one or more of the target audio and the input audio, generating the key parameters; and configuring a second neural network, trained to be configured by the key parameters, with the key parameters to cause the second neural network to perform a signal transformation of the input audio, to produce output audio having an output audio characteristic corresponding to and that matches the target audio characteristic.

Abstract: A frequency domain long-term prediction system and method for estimating and applying an optimum long term predictor. Embodiments of the system and method include determining parameters of a single-tap predictor using a frequency-domain analysis having an optimality criteria based on spectral flatness measure. Embodiments of the system and method also include determining parameters of the long-term predictor by accounting for the performance of the vector quantizer in quantizing the various subbands. In some embodiments other encoder metrics (such as signal tonality) are used as well. Other embodiments of the system and method include determining the optimal parameters of the long-term predictor by accounting for some of the decoder operation. Other embodiments of the system and method include extending a 1-tap predictor to a k-th order predictor by convolving the 1-tap predictor with a pre-set filter and selecting from a table of such pre-set filters based on a minimum energy criteria.

Abstract: An audio signal encoding method is provided comprising: receiving first and second audio signal frames; processing a second portion of the first audio signal frame and a first portion of the second audio signal frame using an orthogonal transformation to determine in part a first intermediate encoding result; and processing the first intermediate encoding result using an orthogonal transformation to determine a set of spectral coefficients that corresponds to at least a portion of the first audio signal frame.

Abstract: A method of encoding an audio signal is provided comprising: applying multiple different time-frequency transformations to an audio signal frame; computing measures of coding efficiency across multiple frequency bands for multiple time-frequency resolutions; selecting a combination of time-frequency resolutions to represent the frame at each of the multiple frequency bands based at least in part upon the computed measures of coding efficiency; determining a window size and a corresponding transform size; determining a modification transformation; windowing the frame using the determined window size; transforming the windowed frame using the determined transform size; modifying a time-frequency resolution within a frequency band of the transform of the windowed frame using the determined modification transformation.

Abstract: An audio signal encoding method is provided comprising: receiving first and second audio signal frames; processing a second portion of the first audio signal frame and a first portion of the second audio signal frame using an orthogonal transformation to determine in part a first intermediate encoding result; and processing the first intermediate encoding result using an orthogonal transformation to determine a set of spectral coefficients that corresponds to at least a portion of the first audio signal frame.

Abstract: A method of encoding an audio signal is provided comprising: applying multiple different time-frequency transformations to an audio signal frame; computing measures of coding efficiency across multiple frequency bands for multiple time-frequency resolutions; selecting a combination of time-frequency resolutions to represent the frame at each of the multiple frequency bands based at least in part upon the computed measures of coding efficiency; determining a window size and a corresponding transform size; determining a modification transformation; windowing the frame using the determined window size; transforming the windowed frame using the determined transform size; modifying a time-frequency resolution within a frequency band of the transform of the windowed frame using the determined modification transformation.

Abstract: Systems and methods discussed herein can provide three-dimensional audio virtualization with sweet spot adaptation. In an example, an audio processor circuit can be used to update audio signals for sweet spot adaptation based on information from at least one depth sensor or camera about a listener position in a listening environment.

Abstract: Systems and methods discussed herein can provide three-dimensional audio virtualization with sweet spot adaptation. In an example, an audio processor circuit can be used to update audio signals for sweet spot adaptation based on information from at least one depth sensor or camera about a listener position in a listening environment.

Abstract: An audio encoder can parse a digital audio signal into a plurality of frames, each frame including a specified number of audio samples, perform a transform of the audio samples of each frame to produce a plurality of frequency-domain coefficients for each frame, partition the plurality of frequency-domain coefficients for each frame into a plurality of bands for each frame, each band having a reshaping parameter that represents a time resolution and a frequency resolution, and encode the digital audio signal to a bit stream that includes the reshaping parameters. For a first band, the reshaping parameter can be encoded using a first alphabet size. For a second band, the reshaping parameter can be encoded using a second alphabet size different from the first alphabet size. Using different alphabet sizes can allow for more compact compression in the bit stream.

Abstract: Systems and methods discussed herein can provide three-dimensional audio virtualization with sweet spot adaptation. In an example, an audio processor circuit can be used to update audio signals for sweet spot adaptation based on information from at least one depth sensor or camera about a listener position in a listening environment.

Abstract: A transform-based codec and method with energy smoothing for mitigating vector quantization errors (such as “birdies”) during the encoding process. Embodiments of the codec and method use an encoder to apply in combination an orthogonal transformation and a vector permutation to frequency transform coefficients. In some embodiments the transformation is performed first followed by the permutation and in other embodiments the order is reversed. The order used is reversed at the decoder. A smoothing parameter containing the level of energy smoothing to be applied is passed from the encoder to the decoder and used by both to compute a transform matrix and an inverse transform matrix. In some embodiments the transform matrix is a fraction Hadamard matrix that is invertible, energy preserving, controllable, and stable.

Abstract: An audio signal encoding method is provided comprising: receiving first and second audio signal frames; processing a second portion of the first audio signal frame and a first portion of the second audio signal frame using an orthogonal transformation to determine in part a first intermediate encoding result; and processing the first intermediate encoding result using an orthogonal transformation to determine a set of spectral coefficients that corresponds to at least a portion of the first audio signal frame.

Abstract: A method of encoding an audio signal is provided comprising: applying multiple different time-frequency transformations to an audio signal frame; computing measures of coding efficiency across multiple frequency bands for multiple time-frequency resolutions; selecting a combination of time-frequency resolutions to represent the frame at each of the multiple frequency bands based at least in part upon the computed measures of coding efficiency; determining a window size and a corresponding transform size; determining a modification transformation; windowing the frame using the determined window size; transforming the windowed frame using the determined transform size; modifying a time-frequency resolution within a frequency band of the transform of the windowed frame using the determined modification transformation.

Abstract: An audio encoder can parse a digital audio signal into a plurality of frames, each frame including a specified number of audio samples, perform a transform of the audio samples of each frame to produce a plurality of frequency-domain coefficients for each frame, partition the plurality of frequency-domain coefficients for each frame into a plurality of bands for each frame, each band having a reshaping parameter that represents a time resolution and a frequency resolution, and encode the digital audio signal to a bit stream that includes the reshaping parameters. For a first band, the reshaping parameter can be encoded using a first alphabet size. For a second band, the reshaping parameter can be encoded using a second alphabet size different from the first alphabet size. Using different alphabet sizes can allow for more compact compression in the bit stream.

Abstract: A frequency domain long-term prediction system and method for estimating and applying an optimum long term predictor. Embodiments of the system and method include determining parameters of a single-tap predictor using a frequency-domain analysis having an optimality criteria based on spectral flatness measure. Embodiments of the system and method also include determining parameters of the long-term predictor by accounting for the performance of the vector quantizer in quantizing the various subbands. In some embodiments other encoder metrics (such as signal tonality) are used as well. Other embodiments of the system and method include determining the optimal parameters of the long-term predictor by accounting for some of the decoder operation. Other embodiments of the system and method include extending a 1-tap predictor to a k-th order predictor by convolving the 1-tap predictor with a pre-set filter and selecting from a table of such pre-set filters based on a minimum energy criteria.

Abstract: A transform-based codec and method with energy smoothing for mitigating vector quantization errors (such as “birdies”) during the encoding process. Embodiments of the codec and method use an encoder to apply in combination an orthogonal transformation and a vector permutation to frequency transform coefficients. In some embodiments the transformation is performed first followed by the permutation and in other embodiments the order is reversed. The order used is reversed at the decoder. A smoothing parameter containing the level of energy smoothing to be applied is passed from the encoder to the decoder and used by both to compute a transform matrix and an inverse transform matrix. In some embodiments the transform matrix is a fraction Hadamard matrix that is invertible, energy preserving, controllable, and stable.