Bose Corporation

Michael Patrick O'Connell

Joseph H Cattell

David J Warkentin

Ricardo Federico Carreras

Lei Cheng

Ole Mattis Nielsen

Brandon Lee Olmos

Dale McElhone

Christopher James Mulhearn

Daniel M Gauger, Jr

Ryan terMeulen

Christopher R Paetsch

Stephen R O'Dea

Jeffrey M Ellenbogen

Jonathan Zonenshine

Adam C Furman

Barret Lippey

William Berardi

Ellen I Searl

James F Shanley

Dale Ian McElhone

Dale Mcelhone

Ryan Termeulen

Chrisopher R Paetsch

Various aspects include a wearable audio device having active noise reduction (ANR). In some cases, a method for processing audio signals includes receiving a noise reduction signal configured to modify an audio signal and generate a noise reduced audio signal, the noise reduction signal having a nominal loop gain; and generating an adjusted noise reduction signal in response to a detected adverse low frequency event, the adjusted noise reduction signal having a modulated loop gain configured to reduce artifacts in the noise reduced audio signal.

Wearable active noise reduction (ANR) device having low frequency feedback loop modulation

Various implementations include a computational architecture for a personal active noise reduction (ANR) device. The device includes a communication interface that receives an audio stream, a driver, a microphone system and an ANR processing platform. The platform includes a first DSP configured to: receive the audio stream and signals from the microphone system, perform ANR on the audio stream according to a set of parameters in the first DSP, and output a processed audio stream. The platform includes a second DSP configured to: generate state data in response to an analysis of the source audio stream, signals from the microphone system, and the processed audio stream; and alter the operational parameters on the first DSP. The platform includes a general purpose processor configured to characterize a malfunction in response to instability or error condition events detected by the second DSP.

Computational architecture for active noise reduction device

Various aspects include a wearable audio device having active noise reduction (ANR). In some cases, an ANR system for a wearable audio device includes: a fixed filter that receives a signal from a feedback microphone and outputs a noise reduction signal, where the fixed filter is configured to provide ANR with a nominal loop gain; and a tunable filter that outputs an adjusted noise reduction signal by modulating the nominal loop gain in response to low frequency noise being detected in the noise reduction signal, where modulating the nominal loop gain includes reducing low frequency ANR performance.

Various aspects include active noise reduction (ANR) devices and approaches, one approach including: receiving an input signal representing audio captured by a feedforward microphone of an ANR headphone; receiving an error signal representing audio captured by an error measurement sensor; generating an anti-noise signal configured to reduce a noise signal over a frequency range; and applying a gain to at least one of the input signal or the anti-noise signal over the frequency range based on the error signal, wherein the applied gain is configured to enhance noise reduction for a plurality of users having distinct fits for the ANR headphone.

Gain-adaptive active noise reduction (ANR) device

Various implementations include a method for implementing a computational architecture for a personal active noise reduction (ANR) device. A method includes receiving a source audio stream with a first DSP and performing ANR on the source audio stream utilizing operational parameters stored in the first DSP; outputting a processed audio stream from the first DSP; generating state data with a second DSP in response to an analysis of at least one of the source audio stream, microphone inputs and the processed audio stream, and communicating signals to the first DSP over a common bus coupled to the first and second DSPs to alter the operational parameters in the first DSP; and utilizing a general purpose processor coupled to both the first DSP and the second DSP to communicate control signals with a communication interface, process state data from the second DSP, and alter the operational parameters in the first DSP.

Aspects of the present disclosure provide methods, apparatuses, and systems for closed-loop sleep protection and/or sleep regulation. According to an aspect, a biosignal parameter and ambient noise are measured. The biosignal parameter is used to determine sleep condition of a subject. The sleep condition is determined based on one or more of personalized sleep data or historical sleep data collected using a subset of society. Based on the sleep condition, an arousal threshold is determined. Based on the ambient noise and the determined sleep condition, one or more actions are taken to regulate sleep and avoid sleep disruption.

Biometric feedback as an adaptation trigger for active noise reduction, masking, and breathing entrainment

Various aspects include a wearable audio device having active noise reduction (ANR), where the ANR device includes: a feedback microphone; an electroacoustic transducer; and a feedback compensator configured to output a noise reduction signal to the electroacoustic transducer in response to a feedback signal from the feedback microphone, wherein the feedback compensator includes a tunable filter that modulates a loop gain in response to an adverse low frequency event being detected in the noise reduction signal outputted from the tunable filter, wherein the tunable filter is configured to maintain a substantially similar loop gain shape near a low frequency cross-over as the low frequency cross-over changes during loop gain modulation.

Various aspects include active noise reduction (ANR) devices and approaches, one approach including: receiving an input signal representing audio captured by a feedforward microphone of an ANR headphone; receiving an error signal representing audio captured by an error measurement sensor; generating an anti-noise signal configured to reduce a noise signal over a frequency range; and applying a gain to at least one of the input signal or the anti-noise signal over the frequency range based on the error signal, where the gain is calculated by: filtering the anti-noise signal over the frequency range to generate a filtered feedforward signal, and filtering the error signal over the frequency range to generate a filtered error signal; estimating a feedforward path contribution to the error signal; and determining the gain based on a correlation between the filtered error signal and the filtered feedforward signal with the assigned feedforward path contribution to the error signal.

Various implementations include a computational architecture for a personal active noise reduction (ANR) device. The device includes a communication interface that receives an audio stream, a driver, a microphone system and an ANR processing platform. The platform includes a first DSP configured to: receive the audio stream and signals from the microphone system, perform ANR on the audio stream according to a set of parameters in the first DSP, and output a processed audio stream. The platform includes a second DSP configured to: generate state data in response to an analysis of the source audio stream, signals from the microphone system, and the processed audio stream; and alter the operational parameters on the first DSP. The platform includes a general purpose processor configured to: communicate control signals with the communication interface, process state data from the second DSP, and alter the parameters on the first DSP.

Aspects of the present disclosure provide methods, apparatuses, and systems for closed-loop sleep protection and/or sleep regulation. According to an aspect, a biosignal parameter and ambient noise are measured. The biosignal parameter is used to determined sleep condition of a subject. The sleep condition is determined based on: (1) one or more of personalized sleep data, (2) historical sleep data collected for a subset of society, or (3) a combination of both. Based on the sleep condition, an arousal threshold is determined. Based on the ambient noise and the determined sleep condition, one or more actions are taken to regulate sleep and avoid sleep disruption by using sound masking or active noise reduction (ANR).

Active noise reduction (ANR) headphones and associated methods are provided. The ANR headphones may include a memory to store a plurality of profiles each including controller information and acoustic parameters in addition to a profile selection routine executable by a processor of the ANR headphone. The profile selection routine may be configured to identify acoustic characteristics of a subject wearing the ANR headphone, compare the acoustic characteristics of the subject with the acoustic parameters of the plurality of profiles, select a profile from the plurality of profiles based on the comparison between the acoustic characteristics of the subject with the acoustic parameters of the selected profile, and provide the controller information of the selected profile to a noise reduction circuit of the ANR headphone.

Systems and methods of active noise reduction in headphones

The technology described in this document can be embodied in a method that includes receiving an input signal representing audio captured by a microphone of an active noise reduction (ANR) headphone, and processing, by a first compensator, a first frequency range of the input signal to generate a first signal for an acoustic transducer of the ANR headphone. The method also includes processing, by a second compensator disposed in parallel to the first compensator, a second frequency range of the input signal to generate a second signal for the acoustic transducer. The first frequency range includes frequencies higher than the frequencies in the second frequency range. The method also includes detecting, by one or more processing devices, that the second signal satisfies a threshold condition, and attenuating the second signal responsive to determining that the second signal satisfies the threshold condition.

Parallel compensation in active noise reduction devices

The technology described in this document can be embodied in a method that includes receiving an input signal representing audio captured by one or more sensors of an active noise reduction (ANR) headphone, and generating, based on the input signal, a first signal by a compensator disposed in an ANR signal flow path. The method also includes determining one or more characteristics of the first signal, and selecting, based on the one or more characteristics of the first signal, a plurality of filter coefficients for a digital filter disposed in series with the compensator in the ANR signal flow path. The filter coefficients are selected in accordance with a target frequency response of the digital filter. The method further includes generating, by processing the input signal using the plurality of filter coefficients of the digital filter, a feedback control signal for an electroacoustic transducer of the ANR headphone.

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Northborough, MA, United States of America

Michael Patrick O'Connell