Cirrus Logic Inc.

Acoustic Technologies, Inc.

Cirrus Logic International Semiconductor Limited

Seth Suppappola

Narayan Kovvali

Samuel P Ebenezer

Ghassan Maalouli

Ying Li

Franklyn H Story

Justin Lamar Allen

Clifton Cordes

Khosrow Lashkari

Wilbur Lawrence

Nima Yousefian Jazi

Nima Yousefian

Robert Winston Nowlin

Venkat Anant

An estimator of direction of arrival (DOA) of speech from a far-field talker to a device in the presence of room reverberation and directional noise includes audio inputs received from multiple microphones and one or more beamformer outputs generated by processing the microphone inputs. A first DOA estimate is obtained by performing generalized cross-correlation between two or more of the microphone inputs. A second DOA estimate is obtained by performing generalized cross-correlation between one of the one or more beamformer outputs and one or more of: the microphone inputs and other of the one or more beamformer outputs. A selector selects the first or second DOA estimate based on an SNR estimate at the microphone inputs and a noise reduction amount estimate at the beamformer outputs. The SNR and noise reduction estimates may be obtained based on the detection of a keyword spoken by a desired talker.

Beamformer enhanced direction of arrival estimation in a reverberant environment with directional noise

A system performs pole-zero or IIR modeling and estimation of an inter-microphone transfer function between first and second microphones that output respective first and second microphone signals. The system includes a first adaptive FIR filter to which the first microphone signal is provided, a delay element that delays the second microphone signal by a predetermined delay amount, and a second adaptive FIR filter to which the delayed second microphone signal is provided. A first coefficient of the second adaptive FIR filter is constrained to a fixed non-zero value. The filters are jointly adapted to minimize an error signal that is a difference of the two filters outputs. The delay is small: approximately the acoustic propagation delay between the two microphones and is not determined by the environmental reverberation characteristics. The error signal may serve as a noise reference in a noise canceller, for implementing far-field beamforming with low delay.

Pole-zero blocking matrix for low-delay far-field beamforming

A multi-microphone algorithm for detecting and differentiating interference sources from desired talker speech in advanced audio processing for smart home applications is described. The approach is based on characterizing a persistent interference source when sounds repeated occur from a fixed spatial location relative to the device, which is also fixed. Some examples of such interference sources include TV, music system, air-conditioner, washing machine, and dishwasher. Real human talkers, in contrast, are not expected to remain stationary and speak continuously from the same position for a long time. The persistency of an acoustic source is established based on identifying historically-recurring inter-microphone frequency-dependent phase profiles in multiple time periods of the audio data. The detection algorithm can be used with a beamforming processor to suppress the interference and for achieving voice quality and automatic speech recognition rate improvements in smart home applications.

Persistent interference detection

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

A method and apparatus to determine a direction of arrival (DOA) of a talker in the presence of a source of spatially-coherent noise. A time sequence of audio samples that include the spatially-coherent noise is received and buffered. Aided by previously known data, a trigger point is detected in the time sequence of audio samples when the talker begins to talk. The buffered time sequence of audio samples is separated into a noise segment and a signal-plus-noise segment based on the trigger point. For each direction of a plurality of distinct directions: an energy difference is computed for the direction between the noise segment and the signal-plus-noise segment, and the DOA of the talker is selected as the direction of the plurality of distinct directions having a largest of the computed energy differences.

Data aided method for robust direction of arrival (DOA) estimation in the presence of spatially-coherent noise interferers

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

Noise sources may be identified as either an interference source, such as a television, or a talker source by analyzing phase information of the microphone signals. A phase delay variance may be computed from pairs of microphone signals. A profile of an interference source may be learned over time by updating a stored profile when the phase delay variance is below a threshold. The stored profile may be used to identify interference sources received by the microphones by determining a correlation between the microphone signals and the stored profile. When an interference source is detected, control parameters may be generated to control a beamformer to reduce contribution of the interference source to an output audio signal. The output audio signal may be used for speech processing, such as in a smart home device.

Temporal and spatial detection of acoustic sources

Test apparatus measuring relative frequency response of first and second microphones includes a rotatable carrier. First and second microphones are sealingly clamped against a mounting surface of the carrier aligned with first and second apertures therein, such apertures lying equidistant from, and on opposite sides of, the carrier's axis of rotation. The carrier initially positions the first microphone closest to an audible signal source, and the responses of the microphones to an audible excitation signal are measured. The carrier is rotated 180 degrees, and the measurements are repeated. Elongated strips of gasket material are used to align the microphones and to form a seal with the carrier. When microphones are mounted deep within an audio device, the audio device is sealingly clamped against a mounting plate, sequentially aligning the mounting plate aperture with first and second apertures of the audio device housing corresponding to first and second microphones disposed therein.

Apparatus and method for measuring relative frequency response of audio device microphones

A telephone includes a transmit channel and a receive channel, each including a bank of sub-band filters having a VAD coupled one to each sub-band filter. Each VAD measures the spectral energy in a sub-band, compares the spectral energy to a first threshold, and produces an output signal representative of whether or not the first threshold is exceeded. The voice activity detector also includes a threshold circuit for calculating a dynamically adjustable noise threshold based upon averaged measured spectral energy. A wide band or system VAD monitors echo canceling circuitry to detect voice activity and double talk.

Distributed VAD control system for telephone

A system includes a loudspeaker, a microphone, an echo canceling circuit, and an accelerometer coupled to the loudspeaker for providing a reference signal, a(n), to the echo canceling circuit. Preferably, the accelerometer is attached to the loudspeaker. A speaker signal, x(n), is used to drive the loudspeaker and the system also includes a switch for coupling either a(n) or x(n) to the echo canceling circuit, depending upon the volume or loudness of the sounds involved.

Acoustic echo canceler using an accelerometer

A background noise estimate based upon a modified Doblinger noise estimate is used for modulating the output of a pseudo-random phase spectrum generator to produce the comfort noise. The circuit for estimating noise includes a smoothing filter having a slower time constant for updating the noise estimate during noise than during speech. Comfort noise is smoothly inserted by basing the amount of comfort noise on the amount of noise suppression. A discrete inverse Fourier transform converts the comfort noise back to the time domain and overlapping windows eliminate artifacts that may have been produced during processing.

Comfort noise generator using modified Doblinger noise estimate

Comfort noise is derived from a white noise signal by filtering the white noise signal in a QMF bank to produce comfort noise signal that is selectively coupled to at least one channel in a telephone. Preferably, a plurality of QMF banks are used and the magnitude of the white noise into each filter is controlled in accordance with the magnitude of the signal in a corresponding analysis sub-band in a channel. In accordance with another aspect of the invention, the signals from higher frequency analysis sub-bands are combined and control a single input to a QMF bank, thereby increasing the low frequency resolution of the comfort noise. In accordance with another aspect of the invention, the QMF banks are cascaded upwardly (the output of one bank is coupled to the low pass input of the next bank), which also enhances the low frequency resolution of the comfort noise.

Comfort noise generator

A path change is detected by multiplying the energy of a signal on the output of a summation circuit in one channel of a telephone by a constant to produce a product. The product is compared with the energy of a signal on the input of the summation circuit. A path change is indicated when the energy of the product exceeds the energy of a signal on the input of the summation circuit. The comparison is made in successive frames of an audio signal and a path change is indicated when the energy of a signal on the input of the summation circuit is exceeded in two or more successive frames.

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Tempe, AZ, United States of America

Seth Suppappola