Audience, Inc.

Knowles Electronics, Inc.

Qualcomm Incorporated

Ye Jiang

Carlo Murgia

Mark Every

Carlos M Avendano

Ludger Solbach

Michael M Goodwin

Mark Robert Every

Peter Santos

Karim Younes

Erik Visser

Lae-Hoon Kim

Jean Laroche

Asif Mohammad

David Klein

Ian Ernan Liu

Sridhar Krishna Nemala

Umit Yapanel

Matthew Cowan

Hong You

An apparatus includes multiple microphones to generate audio signals based on sound of a far-field acoustic environment. The apparatus also includes a signal processing system to process the audio signals to generate at least one processed audio signal. The signal processing system is configured to update one or more processing parameters while operating in a first operational mode and is configured to use a static version of the one or more processing parameters while operating in the second operational mode. The apparatus further includes a keyword detection system to perform keyword detection based on the at least one processed audio signal to determine whether the sound includes an utterance corresponding to a keyword and, based on a result of the keyword detection, to send a control signal to the signal processing system to change an operational mode of the signal processing system.

Directional processing of far-field audio

Systems and methods for controlling adaptivity of noise cancellation are presented. One or more audio signals are received by one or more corresponding microphones. The one or more signals may be decomposed into frequency sub-bands. Noise cancellation consistent with identified adaptation constraints is performed on the one or more audio signals. The one or more audio signals may then be reconstructed from the frequency sub-bands and outputted via an output device.

Adaptive noise cancellation

Methods for voice sensing and keyword analysis are provided. An example method allows for causing a mobile device to transition to a second power mode, from a first power mode, in response to a first acoustic signal. The method includes authenticating a user based at least in part on a second acoustic signal. While authenticating the user, the second acoustic signal is compared to a spoken keyword. The spoken keyword is analyzed for authentication strength based on the length of the spoken keyword, quality of a series of phonemes used to represent the spoken keyword, and likelihood of the series of phonemes to be detected by a voice sensing. While receiving the first and second acoustic signals, a signal to noise ratio (SNR) is determined. The SNR is used to adjust sensitivity of a detection threshold of a voice sensing.

Voice sensing and keyword analysis

A system utilizing two pairs of microphones for noise suppression. Primary and secondary microphones may be positioned closely spaced to each other to provide acoustic signals used to achieve noise cancellation/suppression. An additional, tertiary microphone may be spaced with respect to either the primary microphone or the secondary microphone in a spread-microphone configuration for deriving level cues from audio signals provided by the tertiary and the primary or secondary microphone. The level cues are expressed via a level difference used to determine one or more cluster tracking control signal(s). The level difference-based cluster tracking signals are used to control adaptation of noise suppression. A noise cancelled primary acoustic signal and level difference-based cluster tracking control signals are used during post filtering to adaptively generate a mask to be applied to a speech estimate signal.

Adaptive noise reduction using level cues

A robust noise reduction system may concurrently reduce noise and echo components in an acoustic signal while limiting the level of speech distortion. The system may receive acoustic signals from two or more microphones in a close-talk, hand-held or other configuration. The received acoustic signals are transformed to frequency domain sub-band signals and echo and noise components may be subtracted from the sub-band signals. Features in the acoustic sub-band signals are identified and used to generate a multiplicative mask. The multiplicative mask is applied to the noise subtracted sub-band signals and the sub-band signals are reconstructed in the time domain.

Multi-microphone robust noise suppression

The present technology provides adaptive noise and echo reduction of an acoustic signal which can overcome or substantially alleviate problems associated with mistaken adaptation of speech and noise models to acoustic echo. The present technology carries out a multi-faceted analysis to identify echo within the near-end acoustic signal to derive an echo model. Echo classification information regarding the derived echo model is then utilized to build near-end speech and noise models. These echo, speech, and noise models are then used to generate one or more signal modifications applied to the acoustic signal to preserve the desired near-end speech signal and reduce the echo and near-end noise signals. By building near-end speech and noise models utilizing echo classification information, the present technology can prevent adaptation of the speech and noise model to the acoustic echo.

Robust noise suppression system in adverse echo conditions

Cross-talk reduction and/or cancellation systems and methods are provided herein. In exemplary embodiments, a far-end acoustic signal is delayed by M samples. Additionally, a cross-talk estimate value for the delayed far-end acoustic signal may be subtracted from an input acoustic signal. The cross-talk estimate value is a scaled version of filter outputs generated by a finite impulse response filter that utilizes predetermined filter coefficients. The filter outputs are scaled using a dynamic gain value.

Cross-talk cancellation

Adaptive noise cancelation

An adaptive power control monitors the noise level within a primary acoustic signal and compares the noise level to a threshold. If the noise level is lower than the threshold, a noise suppression system is deactivated and bypass filtering and cross fading are enabled. If the noise level is higher than the threshold, the noise suppression system is activated.

Adaptive power saving for an audio device

Provided are systems and methods for dynamic detection of changes in signal bandwidth associated with audio samples received by a communication device during handovers, where the communication device is moved through geographical areas served by different wireless network technologies. Based on the detection, operation parameters of an audio processor of the communication device may be adjusted or switched to achieve optimal performance of audio enhancing procedures (e.g., noise suppression) performed by the audio processor and to preserve minimal power consumption.

Dynamic bandwidth change detection for configuring audio processor

Crosstalk reduction and/or cancellation systems and methods are provided herein. In exemplary embodiments, a far-end acoustic signal may be delayed by M samples. Additionally, a crosstalk estimate value for the delayed far-end acoustic signal may be subtracted from an input acoustic signal. The crosstalk estimate value is a scaled version of filter outputs generated by a finite impulse response filter that utilizes predetermined filter coefficients. The filter outputs are scaled using a dynamic gain value.

Crosstalk cancellation systems and methods

An audio device having two pairs of microphones for noise suppression. Primary and secondary microphones of the three microphones may be positioned closely spaced to each other to provide acoustic signals used to achieve noise cancellation/suppression. A tertiary microphone may be spaced with respect to either the primary microphone or the secondary microphone in a spread-microphone configuration for deriving level cues from audio signals provided by the tertiary and the primary or secondary microphone. Signals from two microphones may be used rather than three microphones. The level cues are expressed via an inter-microphone level difference (ILD) used to determine one or more cluster tracking control signal(s). The ILD based cluster tracking signals are used to control adaptation of null-processing noise suppression modules. A noise cancelled primary acoustic signal and ILD based cluster tracking control signals are used during post filtering to adaptively generate a mask to be applied against a speech estimate signal.

Systems and methods for envelope-based acoustic echo cancellation in a communication device are provided. In exemplary embodiments, a primary acoustic signal is received via a microphone of the communication device, and a far-end signal is received via a receiver. Frequency analysis is performed on the primary acoustic signal and the far-end acoustic signal to obtain frequency sub-bands. An echo mask based on magnitude envelopes of the primary and far-end acoustic signals for each frequency sub-band is generated. A noise mask based on at least the primary acoustic signal for each frequency sub-band may also be generated. A combination of the echo mask and noise mask may then be applied to the primary acoustic signal to generate a masked signal. The masked signal is then output.

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Sunnyvale, CA, United States of America

Ye Jiang