Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for coding speech using neural networks. One of the methods includes obtaining a bitstream of parametric coder parameters characterizing spoken speech; generating, from the parametric coder parameters, a conditioning sequence; generating a reconstruction of the spoken speech that includes a respective speech sample at each of a plurality of decoder time steps, comprising, at each decoder time step: processing a current reconstruction sequence using an auto-regressive generative neural network, wherein the auto-regressive generative neural network is configured to process the current reconstruction to compute a score distribution over possible speech sample values, and wherein the processing comprises conditioning the auto-regressive generative neural network on at least a portion of the conditioning sequence; and sampling a speech sample from the possible speech sample values.

Abstract: Techniques of performing linear acoustic echo cancellation performing a phase correction operation on the estimate of the echo signal based on a clock drift between a capture of an input microphone signal and a playout of a loudspeaker signal. Along these lines, the existence of the clock drift, i.e., a small difference in the sampling rates of the input microphone signal and the loudspeaker signal, can cause processing circuitry in a device configured to perform LAEC operations to generate a filter based on the magnitudes of the short-term Fourier transforms (STFTs) of the input microphone signal and the loudspeaker signal. Such a filter is real-valued and results in a positive estimate of the acoustic echo signal included in the input microphone signal. The phase of this estimate may then be aligned with the phase of the input microphone signal.

Abstract: Techniques of source localization and acquisition involve a wide-band joint acoustic source localization and acquisition approach in light of sparse optimization framework based on an orthogonal matching pursuit-based grid-shift procedure. Along these lines, a specific grid structure is constructed with the same number of grid points as compared to the on-grid case, but which is “shifted” across the acoustic scene. More specifically, it is expected that each source will be located close to a grid point in at least one of the set of shifted grids. The sparse solutions corresponding to the set of shifted grids are combined to obtain the source location estimates. The estimated source positions are used as side information to obtain the original source signals.

Abstract: Provided are methods, systems, and apparatus for hierarchical decorrelation of multichannel audio. A hierarchical decorrelation algorithm is designed to adapt to possibly changing characteristics of an input signal, and also preserves the energy of the original signal. The algorithm is invertible in that the original signal can be retrieved if needed. Furthermore, the proposed algorithm decomposes the decorrelation process into multiple low-complexity steps. The contribution of these steps is generally in a decreasing order, and thus the complexity of the algorithm can be scaled.

Abstract: According to an aspect, a method for multi-channel echo cancellation includes receiving a microphone signal and a multi-channel loudspeaker driving signal. The multi-channel loudspeaker driving signal includes a first driving signal that drives a first loudspeaker, and a second driving signal that drives a second loudspeaker. The first driving signal is substantially the same as second driving signal. The microphone signal includes a near-end signal with echo. The method includes determining a unique solution for acoustic transfer functions for a present acoustic scenario based on the microphone signal and the multi-channel loudspeaker driving signal. The acoustic transfer functions include first and second acoustic transfer function. The unique solution is determined based on time-frequency transforms of observations from the present acoustic scenario and at least one previous acoustic scenario.

Abstract: Techniques of performing linear acoustic echo cancellation performing a phase correction operation on the estimate of the echo signal based on a clock drift between a capture of an input microphone signal and a playout of a loudspeaker signal. Along these lines, the existence of the clock drift, i.e., a small difference in the sampling rates of the input microphone signal and the loudspeaker signal, can cause processing circuitry in a device configured to perform LAEC operations to generate a filter based on the magnitudes of the short-term Fourier transforms (STFTs) of the input microphone signal and the loudspeaker signal. Such a filter is real-valued and results in a positive estimate of the acoustic echo signal included in the input microphone signal. The phase of this estimate may then be aligned with the phase of the input microphone signal.

Abstract: The invention relates to a sound processing node for an arrangement of sound processing nodes, the sound processing nodes being configured to receive a plurality of sound signals, wherein the sound processing node comprises a processor configured to generate an output signal on the basis of the plurality of sound signals weighted by a plurality of beamforming weights, wherein the processor is configured to adaptively determine the plurality of beamforming weights on the basis of an adaptive linearly constrained minimum variance beamformer using a transformed version of a least mean squares formulation of a constrained gradient descent approach, wherein the transformed version of the least mean squares formulation of the constrained gradient descent approach is based on a transformation of the least mean squares formulation of the constrained gradient descent approach to the dual domain.

Abstract: Provided are methods and systems for improving the intelligibility of speech in a noisy environment. A communication model is developed that includes noise inherent in the message production and message interpretation processes, and considers that these noises have fixed signal-to-noise ratios. The communication model forms the basis of an algorithm designed to optimize the intelligibility of speech in a noisy environment. The intelligibility optimization algorithm only does something (e.g., manipulates the audio signal) when needed, and thus if no noise is present the algorithm does not alter or otherwise interfere with the audio signals, thereby preventing any speech distortion. The algorithm is also very fast and efficient in comparison to most existing approaches for speech intelligibility enhancement, and therefore the algorithm lends itself to easy implementation in an appropriate device (e.g., cellular phone or smartphone).

Abstract: A method includes: receiving a representation of a soundfield, the representation characterizing the soundfield around a point in space; decomposing the received representation into independent signals; and encoding the independent signals, wherein a quantization noise for any of the independent signals has a common spatial profile with the independent signal.

Abstract: A method includes: receiving a representation of a soundfield, the representation characterizing the soundfield around a point in space; decomposing the received representation into independent signals; and encoding the independent signals, wherein a quantization noise for any of the independent signals has a common spatial profile with the independent signal.

Abstract: The disclosure relates to an apparatus for determining a quality score (MOS) for an audio signal sample, the apparatus comprising: an extractor configured to extract a feature vector from the audio signal sample, wherein the feature vector comprises a plurality of feature values and wherein each feature value is associated to a different feature of the feature vector; a pre-processor configured to pre-process a feature value of the feature vector based on a cumulative distribution function associated to the feature represented by the feature value to obtain a pre-processed feature value; and a processor configured to implement a neural network and to determine the quality score (MOS) for the audio signal sample based on the pre-processed feature value and a set of neural network parameters for the neural network associated to the cumulative distribution function.

Abstract: A sound processing node for an arrangement of sound processing nodes is disclosed. The sound processing nodes being configured to receive a plurality of sound signals, wherein the sound processing node comprises a processor configured to determine a beamforming signal on the basis of the plurality of sound signals weighted by a plurality of weights, wherein the processor is configured to determine the plurality of weights using a transformed version of a linearly constrained minimum variance approach, the transformed version of the linearly constrained minimum variance approach being obtained by applying a convex relaxation to the linearly constrained minimum variance approach.

Abstract: Implementations of independent temporally concurrent video stream coding may include encoding a plurality of input frames from an input video sequence, wherein the plurality of input frames includes a first input frame. Encoding the plurality of input frames may include generating a first plurality of encoded frames based on the plurality of input frames such that the first plurality of encoded frames includes a first encoded I-frame corresponding to the first input frame, and generating a second plurality of encoded frames based on the plurality of input frames such that the second plurality of encoded frames includes a first encoded P-frame corresponding to the first input frame. Implementations of independent temporally concurrent video stream coding may include including the first plurality of encoded frames and the second plurality of encoded frames in an output, and transmitting the output to a decoder.

Abstract: Techniques of rendering high-order ambisonics (HOAs) involve adjusting the weights of a spherical harmonic (SH) expansion of a sound field based on weights of a SH expansion of a direction emphasis function that multiplies a monopole density that, when its product with a Green's function is integrated over the unit sphere, produces the sound field. An advantage of the improved techniques lies in the ability to better reproduce directionality of a given sound field in a computationally manner, whether the sound field is a temporal function or a time-frequency function.

Abstract: Provided are methods, systems, and apparatus for hierarchical decorrelation of multichannel audio. A hierarchical decorrelation algorithm is designed to adapt to possibly changing characteristics of an input signal, and also preserves the energy of the original signal. The algorithm is invertible in that the original signal can be retrieved if needed. Furthermore, the proposed algorithm decomposes the decorrelation process into multiple low-complexity steps. The contribution of these steps is generally in a decreasing order, and thus the complexity of the algorithm can be scaled.

Abstract: Provided are methods, systems, and apparatus for hierarchical decorrelation of multichannel audio. A hierarchical decorrelation algorithm is designed to adapt to possibly changing characteristics of an input signal, and also preserves the energy of the original signal. The algorithm is invertible in that the original signal can be retrieved if needed. Furthermore, the proposed algorithm decomposes the decorrelation process into multiple low-complexity steps. The contribution of these steps is generally in a decreasing order, and thus the complexity of the algorithm can be scaled.

Abstract: A sound processing node for an arrangement of sound processing nodes is disclosed. The sound processing nodes being configured to receive a plurality of sound signals, wherein the sound processing node comprises a processor configured to determine a beamforming signal on the basis of the plurality of sound signals weighted by a plurality of weights, wherein the processor is configured to determine the plurality of weights using a transformed version of a linearly constrained minimum variance approach, the transformed version of the linearly constrained minimum variance approach being obtained by applying a convex relaxation to the linearly constrained minimum variance approach.

Abstract: A method includes: receiving a representation of a soundfield, the representation characterizing the soundfield around a point in space; decomposing the received representation into independent signals; and encoding the independent signals, wherein a quantization noise for any of the independent signals has a common spatial profile with the independent signal.

Abstract: Provided are methods and systems for improving the intelligibility of speech in a noisy environment. A communication model is developed that includes noise inherent in the message production and message interpretation processes, and considers that these noises have fixed signal-to-noise ratios. The communication model forms the basis of an algorithm designed to optimize the intelligibility of speech in a noisy environment. The intelligibility optimization algorithm only does something (e.g., manipulates the audio signal) when needed, and thus if no noise is present the algorithm does not alter or otherwise interfere with the audio signals, thereby preventing any speech distortion. The algorithm is also very fast and efficient in comparison to most existing approaches for speech intelligibility enhancement, and therefore the algorithm lends itself to easy implementation in an appropriate device (e.g., cellular phone or smartphone).

Abstract: Provided are methods and systems for improving the intelligibility of speech in a noisy environment. A communication model is developed that includes noise inherent in the message production and message interpretation processes, and considers that these noises have fixed signal-to-noise ratios. The communication model forms the basis of an algorithm designed to optimize the intelligibility of speech in a noisy environment. The intelligibility optimization algorithm only does something (e.g., manipulates the audio signal) when needed, and thus if no noise is present the algorithm does not alter or otherwise interfere with the audio signals, thereby preventing any speech distortion. The algorithm is also very fast and efficient in comparison to most existing approaches for speech intelligibility enhancement, and therefore the algorithm lends itself to easy implementation in an appropriate device (e.g., cellular phone or smartphone).