Audience, Inc.

Knowles Electronics, Inc.

Mark Every

Carlo Murgia

Carlos M Avendano

Ludger Solbach

Ye Jiang

Michael M Goodwin

David Klein

Karim Younes

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

A robust noise suppression 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 cochlea 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.

Adaptive spatial classifier for multi-microphone systems

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

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

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.

Adaptive noise reduction using level cues

The present technology provides noise reduction of an acoustic signal using a configurable classification threshold which provides a sophisticated level of control to balance the tradeoff between positional robustness and noise reduction robustness. The configurable classification threshold corresponds to a configurable spatial region, such that signals arising from sources within the configurable spatial region are preserved, and signals arising from sources outside it are rejected. In embodiments, the configurable classification threshold can be automatically and dynamically adjusted in real-time based on evaluated environmental conditions surrounding an audio device implementing the noise reduction techniques described herein.

Spatial selectivity noise reduction tradeoff for multi-microphone systems

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

A method, system, and computer program for enhancing a signal are presented. The signal is received, and energy estimates of the signal may be determined. At least one characteristic of the signal may be inferred based on the energy estimates. A mask may be generated based, in part, on the at least one characteristic. In turn, the mask may be applied to the signal to produce an enhanced signal, which may be outputted.

System and method for enhancing a monaural audio signal

The present technology provides adaptive noise reduction of an acoustic signal using a sophisticated level of control to balance the tradeoff between speech loss distortion and noise reduction. The energy level of a noise component in a sub-band signal of the acoustic signal is reduced based on an estimated signal-to-noise ratio of the sub-band signal, and further on an estimated threshold level of speech distortion in the sub-band signal. In embodiments, the energy level of the noise component in the sub-band signal may be reduced to no less than a residual noise target level. Such a target level may be defined as a level at which the noise component ceases to be perceptible.

Method for jointly optimizing noise reduction and voice quality in a mono or multi-microphone system

Systems and methods for providing single microphone noise suppression fallback are provided. In exemplary embodiments, primary and secondary acoustic signals are received. A single microphone noise estimate may be generated based on the primary acoustic signal, while a dual microphone noise estimate may be generated based on the primary and secondary acoustic signals. A combined noise estimate based on the single and dual microphone noise estimates is then determined. Using the combined noise estimate, a gain mask may be generated and applied to the primary acoustic signal to generate a noise suppressed signal. Subsequently, the noise suppressed signal may be output.

Growing community of inventors

Palo Alto, CA, United States of America

Mark Every