Abstract: A group of devices acquire audio input of a sound, such as speech, using respective microphones. For pairs of devices in the group, intensity of energy of audio input at each of the devices in the pair is used to determine first proximity data. Relative differences in time-of-arrival of the sound at the devices in the pair is used to determine second proximity data. The first and second proximity data are used to determine an estimated closest device of the pair with respect to the sound. Comparison of the first proximity data to the second proximity also allows a confidence value to be associated with the estimated closest device. The estimated closest device with the greatest confidence value may be selected for use to acquire audio input, present output, and so forth. Additional techniques such as beamforming techniques may be applied to the audio input from the selected device.

Abstract: A system configured to perform distributed echo cancellation processing to attenuate feedback echo from occurring when two devices are acoustically coupled during a communication session. To reduce the feedback echo, one of the devices is configured as a hub device and receives microphone signals, synchronizes the microphone signals, and generates a mixed microphone signal. To enable distributed echo cancellation, the system includes bidirectional feedback link(s) between the hub device and each device synchronized with the hub device. For example, a first bidirectional feedback link sends a microphone signal from a second device to the hub device and sends the mixed microphone signal from the hub device to the second device, which the second device uses to perform echo cancellation. In addition, a second bidirectional feedback link sends a playback signal from the hub device to the second device and sends the output of echo cancellation back to the hub device.

Abstract: A system configured to perform low input-output latency noise reduction in a frequency domain is provided. The real-time noise reduction algorithm performs frame by frame processing of a single-channel noisy acoustic signal to estimate a gain function. Accurate noise power estimates are achieved with the help of minimum statistics approach followed by a voice activity detector. The noise power and gain values are smoothed to remove any external artifacts and avoid background noise modulations. The gain values for individual frequency bands are weighted and smoothed to reduce distortion. To obtain distortionless output speech, the system performs curve fitting by separating the frequency bands into multiple groups and applying a Savitzky-Golay filter to each group. The final gain values generated by these filters are multiplied with the noisy speech signal to obtain a clean speech signal.

Abstract: A system configured to improve audio processing by performing dereverberation and noise reduction during a communication session. The system may apply a two-channel dereverberation algorithm by calculating coherence-to-diffuse ratio (CDR) values and calculating dereverberation (DER) gain values based on the CDR values. While the DER gain values may be calculated at a first stage within the pipeline, the device may apply the DER gain values at a second stage within the pipeline. For example, the device may calculate the DER gain values prior to performing residual echo suppression (RES) processing but may apply the DER gain values after performing RES processing, in order to avoid excessive attenuation of the local speech. In addition to removing reverberation, the DER gain values also remove diffuse noise components, reducing an amount of noise reduction required. Thus, the device may soften noise reduction when the DER gain values are applied.

Abstract: A system configured to improve audio processing by performing dereverberation and noise reduction during a communication session. The system may apply a two-channel dereverberation algorithm by calculating coherence-to-diffuse ratio (CDR) values and calculating dereverberation (DER) gain values based on the CDR values. While the device calculates the DER gain values prior to performing acoustic echo cancellation (AEC) processing, the device applies the DER gain values after performing residual echo suppression (RES) processing in order to avoid excessive attenuation of the local speech. To improve output speech quality, the device does not apply the DER gain values for nonreverberant signals, when a signal-to-noise ratio (SNR) value is too low, and/or when far-end talk (e.g., remote speech) is present. Dereverberation processing is further improved by using frequency dependent parameters to calculate the DER gain values and by adjusting other gain values when the DER gain values are applied.

Abstract: A multi-channel acoustic echo cancellation (AEC) system that includes a residual echo suppressor (RES) that dynamically controls an amount of attenuation to reduce distortion of local speech during double-talk conditions. The RES determines when double-talk conditions are present based on an echo return loss enhancement (ERLE) value. When the ERLE value is above a first threshold value but below a second threshold value, the RES reduces an amount of attenuation applied while generating an RES mask to pass local speech without distortion. When the ERLE value is below the first threshold value or above the second threshold value, the RES applies full attenuation while generating the RES mask in order to suppress a residual echo signal. To further improve RES processing, the RES may apply smoothing across time, smoothing across frequencies, or apply extra echo suppression processing to further attenuate the residual echo signal.