Abstract: An example audio decoding device includes a memory configured to store at least a portion of a coded audio bitstream; and one or more processors configured to: decode, based on the coded audio bitstream, a representation of a soundfield; decode, based on the coded audio bitstream, a syntax element indicating a selection of either a head-related transfer function (HRTF) or a binaural room impulse response (BRIR); and render, using the selected HRTF or BRIR, speaker feeds from the soundfield.

Abstract: A training system produces a resource-efficient machine-trained model via a training architecture that employs plural processing paths. Some of the processing paths incorporate the use of auxiliary information that imparts external knowledge about source items being processed. The training architecture also employs contrastive learning that operates at different respective levels within the training architecture. For instance, the training architecture uses encoder-level contrastive learning to compare output information generated by different encoders within the training architecture. The training architecture uses decoder-level contrastive learning to compare output information produced by different decoders within the training architecture. An inference-stage system performs an application task using the model produced by the training system.

Abstract: Systems and methods for enhancing a headset user's own voice include at least two outside microphones, an inside microphone, audio input components operable to receive and process the microphone signals, a voice activity detector operable to detect speech presence and absence in the received and/or processed signals, and a cross-over module configured to generate an enhanced voice signal. The audio processing components includes a low frequency branch comprising low pass filter banks, a low frequency spatial filter, a low frequency spectral filter and an equalizer, and a high frequency branch comprising highpass filter banks, a high frequency spatial filter, and a high frequency spectral filter.

Abstract: An active noise control system selects one reference sensor providing a reference signal with the largest coherence to a noise signal, among a plurality of available reference sensors, as a first entry of a reference sensor set. After selecting the first entry, the active noise control system repeats a process in which a sensor capable of providing the largest information quantity to a current reference sensor set among remaining sensors is selected as a new entry of a reference sensor set, until a desired number of sensors is reached or a desired control level is reached. When the reference sensor set is determined, the active noise control system utilizes the entries of the reference sensor set to generates a noise control signal suitable for canceling the noise signal.

Abstract: An electronic apparatus is provided. The electronic apparatus includes a microphone, a communication interface including circuitry and a processor configured to, based on identifying that a trigger word is included in a first sound signal received through the microphone, enter a voice recognition mode, identify a gain value for adjusting an intensity of the first sound signal to be in a predetermined intensity range based on the intensity of the first sound, adjust an intensity of a second sound signal received through the microphone in the voice recognition mode based on the identified gain value, and control the communication interface to transmit a user command obtained based on voice recognition regarding the adjusted second sound signal, to an external apparatus.

Abstract: A method, computer program product, and computing system for generating a plurality of acoustic relative transfer functions for a plurality of audio acquisition devices of an audio recording system deployed in an acoustic environment. The plurality of acoustic relative transfer functions may be encoded into a first embedding of acoustic relative transfer functions and at least a second embedding of acoustic relative transfer functions. Information may be extracted from at least the first embedding of acoustic relative transfer functions.

Abstract: An audio system includes an audio/video receiver, a power supply/wireless audio distribution assembly connected to the audio/video receiver, speaker wire, and speakers compatible with the power supply/wireless audio distribution assembly.

Abstract: A method, computer program product, and computing system for selecting a reference audio acquisition device from a plurality of audio acquisition devices of an audio recording system. Audio encounter information of the reference microphone may be encoded, thus defining encoded reference audio encounter information. A plurality of acoustic relative transfer functions between the reference microphone and the plurality of audio acquisition devices of the audio recording system may be generated. The encoded reference audio encounter information and a representation of the plurality of acoustic relative transfer functions may be transmitted.

Abstract: Multichannel audio playback devices and associated systems and methods are disclosed herein. In some examples, a first playback device is configured to receive a source stream of audio content comprising left, right and center input channels. In a first mode, the first playback device is configured to play back audio via a plurality of transducers based on the left, right, and center input channels. In a second mode, in which the first playback device is bonded to second and third playback devices, the first playback device is configured to (i) play back audio via the plurality of transducers based on at least the center input channel, (ii) cause audio to be played via the second playback device based on at least the right input channel, and (iii) cause audio to be played via the third playback device based on at least the left input channel.

Abstract: A method is described which decodes a downmix matrix for mapping a plurality of input channels of audio content to a plurality of output channels, the input and output channels being associated with respective speakers at predetermined positions relative to a listener position, wherein the downmix matrix is encoded by exploiting the symmetry of speaker pairs of the plurality of input channels and the symmetry of speaker pairs of the plurality of output channels. Encoded information representing the encoded downmix matrix is received and decoded for obtaining the decoded downmix matrix.

Abstract: A multi-channel transformer acoustic model that processes a plurality of audio signals output by microphones of a microphone array and outputs probabilities for acoustic units of an utterance represented in the audio signals. The audio signals represent the individual microphones' respective capturing of the utterance. The multi-channel model may perform self-attention on embeddings of the audio signals and then cross-channel attention across the attended audio signals. The cross-channel attention may involve processing of signals relative to each other to model the relationships across channels within and across time frames. The multi-channel model may include a transducer to perform processing frame-by-frame.

Abstract: A position detection method may include obtaining voice signals during a voice call by at least two voice collecting devices; obtaining position energy information of the voice signals; and identifying a position of the terminal device relative to a user during the voice call, from predefined positions based on the position energy information.

Abstract: A method for processing an audio signal in accordance with a room impulse response is described. The audio signal is processed with an early part of the room impulse response separate from a late reverberation of the room impulse response, wherein the processing of the late reverberation has generating a scaled reverberated signal, the scaling being dependent on the audio signal. The processed early part of the audio signal and the scaled reverberated signal are combined.

Abstract: An audio encoding and decoding method and a related apparatus are provided. The audio encoding method includes: determining a channel combination scheme for a current frame; when the channel combination scheme for the current frame is different from a channel combination scheme for a previous frame, performing segmented time-domain downmix processing on left and right channel signals in the current frame based on the channel combination scheme for the current frame and the channel combination scheme for the previous frame, to obtain a primary channel signal and a secondary channel signal in the current frame; and encoding the obtained primary channel signal and secondary channel signal in the current frame.

Abstract: An audio device having a housing including a first loudspeaker disposed in the housing and oriented to emit sound towards a top of the housing, a second loudspeaker disposed in the housing and oriented to emit sound towards a bottom of the housing, and a third loudspeaker disposed in the housing and oriented to emit sound radially outward from the housing of the audio device. Embodiments may include a microphone array disposed proximate the top of the audio device and encircling the first loudspeaker.

Abstract: To sufficiently suppress noise and reverberation, a convolutional beamformer for calculating, at each time point, a weighted sum of a current signal and a past signal sequence having a predetermined delay and a length of 0 or more such that it increases a probability expressing a speech-likeness of an estimation signals based on a predetermined probability model is acquired where the estimation signals are acquired by applying the convolutional beamformer to frequency-divided observation signals corresponding respectively to a plurality of frequency bands of observation signals acquired by picking up acoustic signals emitted from a sound source, whereupon target signals are acquired by applying the acquired convolutional beamformer to the frequency-divided observation signals.

Abstract: An apparatus, method and computer program is disclosed. The apparatus may comprise a means comprising at least one processor and at least one memory including computer program code, the at least one memory and computer program code configured to, with the at least one processor, to receive multimedia data representing a scene, the multimedia data comprising at least audio data representing an audio component of the scene. Another operation may comprise determining a location of unwanted sound in the scene. Another operation may comprise performing first audio processing to remove at least part of the unwanted sound from the determined location. Another operation may comprise performing second audio processing to add artificial sound associated to the unwanted sound at the determined location.

Abstract: A communication system includes a headset, which is configured to output sound waves to an ear of a user based on an audio signal, as well as a microphone, which is configured to output a microphone signal based on ambient sound. The communication system further contains a processing circuit, which is configured to generate, based on the microphone signal, a signal component of the audio signal, which signal component includes information about the generation of sound waves which interfere destructively with a component of the ambient sound occurring at the ear of the user. In addition, the communication system contains a wireless interface and a control circuit, which is configured to activate the processing circuit as a function of an operating state of the wireless interface.

Abstract: A method for mapping a plurality of input channels of an input channel configuration to output channels of an output channel configuration includes providing a set of rules associated with each input channel of the plurality of input channels, wherein the rules define different mappings between the associated input channel and a set of output channels. For each input channel of the plurality of input channels, a rule associated with the input channel is accessed, determination is made whether the set of output channels defined in the accessed rule is present in the output channel configuration, and the accessed rule is selected if the set of output channels defined in the accessed rule is present in the output channel configuration. The input channels are mapped to the output channels according to the selected rule.

Abstract: Developed and presented herein are embodiments of a new end-to-end approach for audio denoising, from a synthesis perspective. Instead of explicitly modelling the noise component in the input signal, embodiments directly synthesize the denoised audio from a generative model (or vocoder), as in text-to-speech systems. In one or more embodiments, to generate the phonetic contents for the autoregressive generative model, it is learned via a variational autoencoder with discrete latent representations. Furthermore, in one or more embodiments, a new matching loss is presented for the denoising purpose, which is masked on when the corresponding latent codes differ. As compared against other method on test datasets, embodiments achieve competitive performance and can be trained from scratch.