Cirrus Logic Inc.

Cirrus Logic International Semiconductor Limited

Ying Li

Seth Suppappola

Narayan Kovvali

Ghassan Maalouli

Wilbur Lawrence

Nima Yousefian Jazi

Venkat Anant

An acoustic echo path change detector provides a monitoring process in an acoustic echo canceler that removes echo from a microphone signal using an adaptive echo path model that generates an echo estimate from a playback signal. The acoustic echo canceler removes the echo estimate from the microphone signal to provide an echo-canceled output signal. The path change detector receives the microphone signal, the echo estimate and the output signal and determines a rate of change of one or more statistical values dependent on the microphone signal, the echo estimate and the output signal. If the rate of change exceeds a threshold value, the echo path change detector generates an indication that causes a supervisory process to change adaptation of the adaptive echo path model to increase responsiveness to the change in the acoustic echo path, e.g., by increasing the step size.

Echo path change monitoring in an acoustic echo canceler

The reliable differentiation of human and artificial talkers is important for many automatic speaker verification applications, such as in developing anti-spoofing countermeasures against replay attacks for voice biometric authentication. A multi-microphone approach may exploit small movements of human talkers to differentiate between a human talker and an artificial talker. One method of determining the presence or absence of talker movement includes monitoring the variation of the inter-mic frequency-dependent phase profile of the received microphone array data over a period of time. Using spatial information with spectral-based techniques for determining whether an audio source is a human or artificial talker may reduce the likelihood of success of spoofing attacks against a voice biometric authentication system. The anti-spoofing countermeasure may be used in electronic devices including smart home devices, cellular phones, tablets, and personal computers.

Multi-microphone human talker detection

A change in the phase pattern of the inter-mic impulse response (IMIR), determined by a cross power spectral density, may be used to detect the appearance of a new talker or a dramatic movement of the current talker. For example, the phase of the IMIR is dependent on a location of the sound source relative to the microphone array. Any signal originating from a specific location has a specific phase pattern on the IMIR across the frequency domain. By comparing phase patterns of the current cross power spectral density with a recorded talker phase profile, a talker change can be detected. This detection can be used to control signal processing algorithms. For example, when talker change is detected, the step size of an adaptive filter can be increased to track the changes efficiently.

Talker change detection

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Chandler, AZ, United States of America

Ying Li