Abstract: A device capable of motion includes an acoustic echo canceller for cancelling a reference signal from received audio data. The device updates an adaptive filter as the device moves to reflect the changing audio channel between a loudspeaker and a microphone of the device. A step size for changing coefficients of the filter is determined based on its velocity. A number of iterations for updating the filter using a frame of audio data is also determined based on the velocity.

Abstract: A device capable of moving a component of the device motion is capable of determining audio data corresponding to a direction relative to the device (“beamforming”). When the component moves, the device determines a new position of the component and selects one of a set of beamforming filter coefficients corresponding to the position. Using the filter coefficients, the device determines the directional audio data.

Abstract: Residual echo that remains after an echo cancellation process may interfere with speech recognition. If near-end speech is detected in an audio input signal, a controller may attenuate the audio playback signal. Too much attenuation may disturb playback, whereas too little attenuation may not improve speech recognition. Accordingly, features are disclosed for attenuating an audio playback signal based at least in part on residual echo level.

Abstract: A regression-based residual echo suppression (RES) system and process for suppressing the portion of the microphone signal corresponding to a playback of a speaker audio signal that was not suppressed by an acoustic echo canceller (AEC). In general, a prescribed regression technique is used between a prescribed spectral attribute of multiple past and present, fixed-length, periods (e.g., frames) of the speaker signal and the same spectral attribute of a current period (e.g., frame) of the echo residual in the output of the AEC. This automatically takes into consideration the correlation between the time periods of the speaker signal. The parameters of the regression can be easily tracked using adaptive methods. Multiple applications of RES can be used to produce better results and this system and process can be applied to stereo-RES as well.

Abstract: An acoustic echo cancellation technique. The present adaptive acoustic echo cancellation technique employs a plurality of acoustic echo cancellation filters which use different adaptation techniques which may employ different parameters such as step size, to improve both the adaptation algorithm convergence time and misadjustment over previously known acoustic echo cancellation techniques.

Abstract: A regression-based residual echo suppression (RES) system and process for suppressing the portion of the microphone signal corresponding to a playback of a speaker audio signal that was not suppressed by an acoustic echo canceller (AEC). In general, a prescribed regression technique is used between a prescribed spectral attribute of multiple past and present, fixed-length, periods (e.g., frames) of the speaker signal and the same spectral attribute of a current period (e.g., frame) of the echo residual in the output of the AEC. This automatically takes into consideration the correlation between the time periods of the speaker signal. The parameters of the regression can be easily tracked using adaptive methods. Multiple applications of RES can be used to produce better results and this system and process can be applied to stereo-RES as well.

Abstract: A regression-based residual echo suppression (RES) system and process for suppressing the portion of the microphone signal corresponding to a playback of a speaker audio signal that was not suppressed by an acoustic echo canceller (AEC). In general, a prescribed regression technique is used between a prescribed spectral attribute of multiple past and present, fixed-length, periods (e.g., frames) of the speaker signal and the same spectral attribute of a current period (e.g., frame) of the echo residual in the output of the AEC. This automatically takes into consideration the correlation between the time periods of the speaker signal. The parameters of the regression can be easily tracked using adaptive methods. Multiple applications of RES can be used to produce better results and this system and process can be applied to stereo-RES as well.

Abstract: A regression-based residual echo suppression (RES) system and process for suppressing the portion of the microphone signal corresponding to a playback of a speaker audio signal that was not suppressed by an acoustic echo canceller (AEC). In general, a prescribed regression technique is used between a prescribed spectral attribute of multiple past and present, fixed-length, periods (e.g., frames) of the speaker signal and the same spectral attribute of a current period (e.g., frame) of the echo residual in the output of the AEC. This automatically takes into consideration the correlation between the time periods of the speaker signal. The parameters of the regression can be easily tracked using adaptive methods. Multiple applications of RES can be used to produce better results and this system and process can be applied to stereo-RES as well.