Abstract: A head-related transfer function (HRTF) generation system includes one or more processors configured to retrieve first image data of a first ear of a subject, compare the first image data with second image data of a plurality of second ears to identify a particular second ear of the plurality of second ears matching the first ear, identify a template HRTF associated with the particular second ear, and assign an HRTF to the subject based on the template HRTF.

Abstract: An audio control system includes at least one microphone, at least one speaker, and one or more processors. The at least one microphone is at a first position adjacent to an ear of a user and configured to detect a sound field at the first position and output a sound signal indicative of the detected sound field. The at least one speaker is at a second position spaced from the first position and configured to output sound responsive to receiving an audio signal. The one or more processors are configured to generate the audio signal based on the sound signal and a target parameter of the sound field at (i) the first position and (ii) a third position spaced from the first position; and provide the audio signal to the at least one speaker to cause the at least one speaker to output the sound responsive to receiving the audio signal.

Abstract: A spatial-audio recording system includes a processor, and instructions stored in a computer-readable medium that, when read by the processor, cause the processor to perform operations. The operations include retrieving audio data recorded at a number of microphones, determining a recorded signal vector based on the audio data, and initializing values for an operator. The operations further include determining a plurality of waves from directions by performing operations comprising iteratively, until an exit condition is satisfied: initializing or incrementing an index “i”; determining an ith direction using the operator; and updating the operator to correspond to the ith iteration.

Abstract: A spatial-audio recording system includes a spatial-audio recording device including a plurality of microphones, and a computing device. The computing device is configured to determine a plane-wave transfer function for the spatial-audio recording device based on a physical shape of the spatial-audio recording device and to expand the plane-wave transfer function to generate a spherical-harmonics transfer function corresponding to the plane-wave transfer function. The computing device is further configured to retrieve a plurality of signals captured by the microphones, determine spherical-harmonics coefficients for an audio signal based on the plurality of captured signals and the spherical-harmonics transfer function, and generate the audio signal based on the determined spherical-harmonics coefficients.

Abstract: A spatial-audio recording system includes a spatial-audio recording device including a plurality of microphones, and a computing device. The computing device is configured to determine a plane-wave transfer function for the spatial-audio recording device based on a physical shape of the spatial-audio recording device and to expand the plane-wave transfer function to generate a spherical-harmonics transfer function corresponding to the plane-wave transfer function. The computing device is further configured to retrieve a plurality of signals captured by the microphones, determine spherical-harmonics coefficients for an audio signal based on the plurality of captured signals and the spherical-harmonics transfer function, and generate the audio signal based on the determined spherical-harmonics coefficients.

Abstract: A spatial-audio recording system includes a processor, and instructions stored in a computer-readable medium that, when read by the processor, cause the processor to perform operations. The operations include retrieving audio data recorded at a number of microphones, determining a recorded signal vector based on the audio data, and initializing values for an operator. The operations further include determining a plurality of waves from directions by performing operations comprising iteratively, until an exit condition is satisfied: initializing or incrementing an index “i”; determining an ith direction using the operator; and updating the operator to correspond to the ith iteration.

Abstract: This application describes methods of signal processing and spatial audio synthesis. One such method includes accepting an auditory signal and generating an impression of auditory virtual reality by processing the auditory signal to impute a spatial characteristic on it via convolution with a plurality of head-related impulse responses. The processing is performed in a series of steps, the steps including: performing a first convolution of an auditory signal with a characteristic-independent, mixed-sign filter and performing a second convolution of the result of first convolution with a characteristic-dependent, sparse, non-negative filter. In some described methods, the first convolution can be pre-computed and the second convolution can be performed in real-time, thereby resulting in a reduction of computational complexity in said methods of signal processing and spatial audio synthesis.

Abstract: This application describes methods of signal processing and spatial audio synthesis. One such method includes accepting an auditory signal and generating an impression of auditory virtual reality by processing the auditory signal to impute a spatial characteristic on it via convolution with a plurality of head-related impulse responses. The processing is performed in a series of steps, the steps including: performing a first convolution of an auditory signal with a characteristic-independent, mixed-sign filter and performing a second convolution of the result of first convolution with a characteristic-dependent, sparse, non-negative filter. In some described methods, the first convolution can be pre-computed and the second convolution can be performed in real-time, thereby resulting in a reduction of computational complexity in said methods of signal processing and spatial audio synthesis.

Abstract: This application describes methods of signal processing and spatial audio synthesis. One such method includes accepting an auditory signal and generating an impression of auditory virtual reality by processing the auditory signal to impute a spatial characteristic on it via convolution with a plurality of head-related impulse responses. The processing is performed in a series of steps, the steps including: performing a first convolution of an auditory signal with a characteristic-independent, mixed-sign filter and performing a second convolution of the result of first convolution with a characteristic-dependent, sparse, non-negative filter. In some described methods, the first convolution can be pre-computed and the second convolution can be performed in real-time, thereby resulting in a reduction of computational complexity in said methods of signal processing and spatial audio synthesis.

Abstract: A method comprises providing at least one processing unit comprising a decomposing section and a playback section; receiving, at the decomposing section, audio data generated via an array of microphones, the audio data representing an acoustic scene; decomposing the audio data into a plurality of signals representing components of the acoustic scene arriving from a plurality of directions, using the decomposing section; and rendering the audio components for a listener based on the plurality of directions of the audio components, using the playback section.

Abstract: A system for generating and outputting three-dimensional audio data using head-related transfer functions (HRTFs) includes a processor configured to perform operations comprising: using a collection of previously measured HRTFs for audio signals corresponding to multiple directions for at least one subject; performing non-parametric Gaussian process hyper-parameter training on the collection of previously measured HRTFs to generate one or more predicted HRTFs that are different from the previously measured HRTFs; and generating and outputting three-dimensional audio data based on at least the one or more predicted HRTFs.

Abstract: An apparatus comprises a plurality of microphone units including at least a first microphone unit and a second microphone unit, each of the first and second microphone units comprising a microphone, an analog-to-digital converter, and a local memory. The microphone is configured to capture an analog audio signal. The analog-to-digital converter is configured to convert the analog audio signal created by the microphone into a digital audio signal. The local memory is configured to store the digital audio signal. The apparatus further comprises. a controller unit comprising a processor configured to process the digital audio signals. The first microphone unit and the second microphone unit are operatively connected to the controller unit in a series configuration, the second microphone unit being configured to output the digital audio signal to the first microphone unit, and the first microphone unit being configured to output the digital audio signal to the controller unit.

Abstract: This application describes methods of signal processing and spatial audio synthesis. One such method includes accepting an auditory signal and generating an impression of auditory virtual reality by processing the auditory signal to impute a spatial characteristic on it via convolution with a plurality of head-related impulse responses. The processing is performed in a series of steps, the steps including: performing a first convolution of an auditory signal with a characteristic-independent, mixed-sign filter and performing a second convolution of the result of first convolution with a characteristic-dependent, sparse, non-negative filter. In some described methods, the first convolution can be pre-computed and the second convolution can be performed in real-time, thereby resulting in a reduction of computational complexity in said methods of signal processing and spatial audio synthesis.

Abstract: The dereverberation of signals in reverberating environments is carried out via acquiring the representation (image) of spatial distribution of the signals in space of interest and automatic identification of reflections of the source signal in the reverberative space. The technique relies on identification of prominent features at the image, as well as corresponding directions of propagation of signals manifested by the prominent features at the image, and computation of similarity metric between signals corresponding to the prominent features in the image. The time delays between the correlated signals (i.e., source signal and related reflections) are found and the signals are added coherently. Multiple beamformers operate on the source signal and corresponding reflections, enabling one to improve the signal-to-noise ratio in multi-path environments.

Abstract: A system is disclosed for statistical modelling, interpolation, and user-feedback based inference of head-related transfer functions (HRTF) includes a processor performing operations that include using a collection of previously measured head related transfer functions for audio signals corresponding to multiple directions for at least one subject; and performing Gaussian process hyper-parameter training on the collection of audio signals. A method is disclosed for statistical modelling, interpolation, measurement and anthropometry based prediction of head-related transfer functions (HRTF) for a virtual audio system that includes collecting audio signals in transform domain for at least one subject; applying head related transfer functions (HRTF) measurement directions in multiple directions to the collected audio signals; and performing Gaussian hyper-parameter training on the collection of audio signals to generate at least one predicted HRTF.

Abstract: An apparatus comprises a plurality of microphone units including at least a first microphone unit and a second microphone unit, each of the first and second microphone units comprising a microphone, an analog-to-digital converter, and a local memory. The microphone is configured to capture an analog audio signal. The analog-to-digital converter is configured to convert the analog audio signal created by the microphone into a digital audio signal. The local memory is configured to store the digital audio signal. The apparatus further comprises, a controller unit comprising a processor configured to process the digital audio signals. The first microphone unit and the second microphone unit are operatively connected to the controller unit in a series configuration, the second microphone unit being configured to output the digital audio signal to the first microphone unit, and the first microphone unit being configured to output the digital audio signal to the controller unit.

Abstract: A method comprises providing at least one processing unit comprising a decomposing section and a playback section; receiving, at the decomposing section, audio data generated via an array of microphones, the audio data representing an acoustic scene; decomposing the audio data into a plurality of signals representing components of the acoustic scene arriving from a plurality of directions, using the decomposing section; and rendering the audio components for a listener based on the plurality of directions of the audio components, using the playback section.

Abstract: Spherical microphone arrays provide an ability to compute the acoustical intensity corresponding to different spatial directions in a given frame of audio data. These intensities may be exhibited as an image and these images are generated at a high frame rate to achieve a video image if the data capture and intensity computations can be performed sufficiently quickly, thereby creating a frame-rate audio camera. A description is provided herein regarding how such a camera is built and the processing done sufficiently quickly using graphics processors. The joint processing of and captured frame-rate audio and video images enables applications such as visual identification of noise sources, beamforming and noise-suppression in video conferencing and others, by accounting for the spatial differences in the location of the audio and the video cameras. Based on the recognition that the spherical array can be viewed as a central projection camera, such joint analysis can be performed.

Abstract: The dereverberation of signals in reverberating environments is carried out via acquiring the representation (image) of spatial distribution of the signals in space of interest and automatic identification of reflections of the source signal in the reverberative space. The technique relies on identification of prominent features at the image, as well as corresponding directions of propagation of signals manifested by the prominent features at the image, and computation of similarity metric between signals corresponding to the prominent features in the image. The time delays between the correlated signals (i.e., source signal and related reflections) are found and the signals are added coherently. Multiple beamformers operate on the source signal and corresponding reflections, enabling one to improve the signal-to-noise ratio in multi-path environments.

Abstract: Head Related Transfer Functions (HRTFs) of an individual are measured in rapid fashion in an arrangement where a sound source is positioned in the individual's ear channel, while microphones are arranged in the microphone array enveloping the individual's head. The pressure waves generated by the sounds emanating from the sound source reach the microphones and are converted into corresponding electrical signals which are further processed in a processing system to extract HRTFs, which may then be used to synthesize a spatial audio scene. The acoustic field generated by the sounds from the sound source can be evaluated at any desired point inside or outside the microphone array.