Abstract: A method in a biometric authentication system, generating an acoustic stimulus for application to a user’s ear; receiving an audio signal representing a response of the user’s ear canal to the acoustic stimulus; adapting an ear canal response estimate of the user’s ear canal to the acoustic stimulus to reduce an error between the audio signal and the ear canal response estimate; calculating one or more quality metrics, the quality metrics comprising one or more of: an ear canal response estimate quality metric comprising one or more energy characteristics of the ear canal response estimate; an error quality metric derived from the error; an audio response quality metric comprising one or more statistical characteristics of the audio signal; and determining a validity of the audio signal for use in a biometric process based on the quality metrics.

Abstract: 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.

Abstract: Voice biometrics scoring is performed on received asynchronous audio outputs from microphones distributed at ad hoc locations to generate confidence scores that indicate a likelihood of an enrolled user speech utterance in the output, a subset of the outputs is selected based on the confidence scores, and the subset is spatially processed to provide audio output for voice application use. Alternatively, asynchronous spatially processed audio outputs and corresponding biometric identifiers are received from corresponding devices distributed at ad hoc locations, audio frames of the outputs are synchronized using the biometric identifiers, and the synchronized frames are coherently combined. Alternatively, uttered speech associated with respective ad hoc distributed devices is received and non-coherently combined to generate a final output of uttered speech.

Abstract: A method includes extracting, from multiple microphone input, a hyperset of features of acoustic sources, using the extracted features to identify separable clusters associated with acoustic scenarios, and classifying subsequent input as one of the acoustic scenarios using the hyperset of features. The acoustic scenarios include a desired spatially moving/non-moving talker, and an undesired spatially moving/non-moving acoustic source. The hyperset of features includes both spatial and voice biometric features. The classified acoustic scenario may be used in a robotics application or voice assistant device desired speech enhancement or interference signal cancellation. Specifically, the classification of the acoustic scenarios can be used to adapt a beamformer, e.g., step size adjustment. The hyperset of features may also include visual biometric features extracted from one or more cameras viewing the acoustic sources.

Abstract: Voice biometrics scoring is performed on received asynchronous audio outputs from microphones distributed at ad hoc locations to generate confidence scores that indicate a likelihood of an enrolled user speech utterance in the output, a subset of the outputs is selected based on the confidence scores, and the subset is spatially processed to provide audio output for voice application use. Alternatively, asynchronous spatially processed audio outputs and corresponding biometric identifiers are received from corresponding devices distributed at ad hoc locations, audio frames of the outputs are synchronized using the biometric identifiers, and the synchronized frames are coherently combined. Alternatively, uttered speech associated with respective ad hoc distributed devices is received and non-coherently combined to generate a final output of uttered speech.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: Methods and apparatus are provided for spread spectrum communication having spectrum awareness and interference mitigation based on parameterizing an input signal having multiple mixed baseband signals. The method includes non-linearly transforming the input signal, removing carrier effects, removing higher order terms by passing the input signal through a low pass filter to produce a linear combination of data symbols and DC components, solving for the DC components, separating a plurality of mixed baseband signals from the input signal, and coordinate transforming each of the separated signals from polar coordinates to a Cartesian coordinates.