Dolby Laboratories Licensing Corporation

Dolby International Ab

David Gunawan

Glenn N Dickins

Dong Shi

Christopher Graham Hines

Kai Lin Li

Erwin Goesnar

Hannes Muesch

Mark R P Thomas

Benjamin John Southwell

Alan Jeffrey Seefeldt

Xuejing Sun

Richard James Cartwright

Daniel Arteaga

Carlos Eduardo Medaglia Dyonisio

Joshua Brandon Lando

Gary Spittle

Michael Eckert

Paul Francis Holmberg

Feng Deng

Ludovic Christophe Malfait

Qianqian Fang

C Phillip Brown

Zhiwei Shuang

Kai Li

Guilin Ma

Chunjian Li

Davide Scaini

Andrew Border

Yen-Liang Shue

Avery Bruni

Olha Michelle Townsend

Carlos Medaglia Dyonisio

Paul Holmberg

Anthony Tucker

Mark Rp Thomas

Some methods may involve receiving a first content stream that includes first audio signals, rendering the first audio signals to produce first audio playback signals, generating first direct sequence spread spectrum (DSSS) signals, generating first modified audio playback signals by inserting the first DSSS signals into the first audio playback signals, and causing a loudspeaker system to play back the first modified audio playback signals, to generate first audio device playback sound. The method(s) may involve receiving microphone signals corresponding to at least the first audio device playback sound and to second through Naudio device playback sound corresponding to second through Nmodified audio playback signals (including second through Nth DSSS signals) played back by second through Nth audio devices, extracting second through NDSSS signals from the microphone signals and estimating at least one acoustic scene metric based, at least partly, on the second through NDSSS signals.

Orchestration of acoustic direct sequence spread spectrum signals for estimation of acoustic scene metrics

Some methods may involve receiving a first content stream that includes first audio signals, rendering the first audio signals to produce first audio playback signals, generating first calibration signals, generating first modified audio playback signals by inserting the first calibration signals into the first audio playback signals, and causing a loudspeaker system to play back the first modified audio playback signals, to generate first audio device playback sound. The method(s) may involve receiving microphone signals corresponding to at least the first audio device playback sound and to second through Nth audio device playback sound corresponding to second through Nth modified audio playback signals (including second through Nth calibration signals) played back by second through Nth audio devices, extracting second through Nth calibration signals from the microphone signals and estimating at least one acoustic scene metric based, at least partly, on the second through Nth calibration signals.

Pervasive acoustic mapping

Some implementations involve receiving, from a first subband domain acoustic echo canceller (AEC) of a first audio device in an audio environment, first adaptive filter management data from each of a plurality of first adaptive filter management modules, each first adaptive filter management module corresponding to a subband of the first subband domain AEC, each first adaptive filter management module being configured to control a first plurality of adaptive filters. The first plurality of adaptive filters may include at least a first adaptive filter type and a second adaptive filter type. Some implementations involve extracting, from the first adaptive filter management data, a first plurality of extracted features corresponding to a plurality of subbands of the first subband domain AEC and estimating a current local acoustic state based, at least in part, on the first plurality of extracted features.

Subband domain acoustic echo canceller based acoustic state estimator

Some implementations involve obtaining a plurality of echo references, the plurality of echo references including at least one echo reference for each audio device of a plurality of audio devices in an audio environment, each echo reference corresponding to audio data being played back by one or more loudspeakers of one audio device of the plurality of audio devices. Some examples involve making an importance estimation for each echo reference of the plurality of echo references. Making the importance estimation may involve determining an expected contribution of each echo reference to mitigation of echo by at least one echo management system of at least one audio device of the audio environment. Some implementations involve selecting, based at least in part on the importance estimation, one or more selected echo references and providing the one or more selected echo references to the at least one echo management system.

Echo reference prioritization and selection

An audio session management method for an audio environment having multiple audio devices may involve receiving, from a first device implementing a first application and by a device implementing an audio session manager, a first route initiation request to initiate a first route for a first audio session. The first route initiation request may indicate a first audio source and a first audio environment destination. The first audio environment destination may correspond with at least a first person in the audio environment, but in some instances will not indicate an audio device. The method may involve establishing a first route corresponding to the first route initiation request. Establishing the first route may involve determining a first location of at least the first person in the audio environment, determining at least one audio device for a first stage of the first audio session and initiating or scheduling the first audio session.

Coordination of audio devices

Methods for echo estimation or echo management (echo suppression or cancellation) on an input audio signal, with at least one of adaptation of a sparse prediction filter set, modification (for example, truncation) of adapted prediction filter impulse responses, generation of a composite impulse response from adapted prediction filter impulse responses, or use of echo estimation and/or echo management resources in a manner determined at least in part by classification of the input audio signal as being (or not being) echo free. Other aspects are systems configured to perform any embodiment of any of the methods.

Echo estimation and management with adaptation of sparse prediction filter set

Methods and systems for performing at least one audio activity (e.g., conducting a phone call or playing music or other audio content) in an environment including by determining an estimated location of a user in the environment in response to sound uttered by the user (e.g., a voice command), and controlling the audio activity in response to determining the estimated user location. The environment may have zones which are indicated by a zone map and estimation of the user location may include estimating in which of the zones the user is located. The audio activity may be performed using microphones and loudspeakers which are implemented in or coupled to smart audio devices.

Estimating user location in a system including smart audio devices

Some methods may involve receiving a first content stream that includes first audio signals, rendering the first audio signals to produce first audio playback signals, generating first direct sequence spread spectrum (DSSS) signals, generating first modified audio playback signals by inserting the first DSSS signals into the first audio playback signals, and causing a loudspeaker system to play back the first modified audio playback signals, to generate first audio device playback sound. The method(s) may involve receiving microphone signals corresponding to at least the first audio device playback sound and to second through Naudio device playback sound corresponding to second through Nmodified audio playback signals (including second through NDSSS signals) played back by second through Nth audio devices, extracting second through NDSSS signals from the microphone signals and estimating at least one acoustic scene metric based, at least partly, on the second through NDSSS signals.

An audio processing method may involve receiving output signals from each microphone of a plurality of microphones in an audio environment, the output signals corresponding to a current utterance of a person and determining, based on the output signals, one or more aspects of context information relating to the person, including an estimated current proximity of the person to one or more microphone locations. The method may involve selecting two or more loudspeaker-equipped audio devices based, at least in part, on the one or more aspects of the context information, determining one or more types of audio processing changes to apply to audio data being rendered to loudspeaker feed signals for the audio devices and causing one or more types of audio processing changes to be applied. In some examples, the audio processing changes have the effect of increasing a speech to echo ratio at one or more microphones.

Acoustic echo cancellation control for distributed audio devices

An audio session management method may involve: determining, by an audio session manager, one or more first media engine capabilities of a first media engine of a first smart audio device, the first media engine being configured for managing one or more audio media streams received by the first smart audio device and for performing first smart audio device signal processing for the one or more audio media streams according to a first media engine sample clock; receiving, by the audio session manager and via a first application communication link, first application control signals from the first application; and controlling the first smart audio device according to the first media engine capabilities, by the audio session manager, via first audio session management control signals transmitted to the first smart audio device via a first smart audio device communication link and without reference to the first media engine sample clock.

Some disclosed teleconferencing methods may involve detecting a howl state during a teleconference. The teleconference may involve two or more teleconference client locations and a teleconference server. The teleconference server may be configured for providing full-duplex audio connectivity between the teleconference client locations. The howl state may be a state of acoustic feedback involving two or more teleconference devices in a teleconference client location. Detecting the howl state may involve an analysis of both spectral and temporal characteristics of teleconference audio data. Some disclosed teleconferencing methods may involve determining which client location is causing the howl state. Some such methods may involve mitigating the howl state and/or sending a howl state detection message.

Howl detection in conference systems

An apparatus and method of transmission control for an audio device. The audio device uses sources other than the microphone to determine nuisance, and uses this to calculate a gain as well as to make the transmit decision. Using the gain results in a more nuanced nuisance mitigation than using the transmit decision on its own.

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Sydney, Australia

David Gunawan