Cypress Semiconductor Corporation

Clearone, Inc.

Clearone Communications, Inc.

Broadcom Corporation

Ashutosh Pandey

David K Lambert

Tracy A Bathurst

Darrin T Thurston

Robert W Zopf

Jes Thyssen

Juin-Hwey Chen

Victor Simileysky

Michael Braithwaite

Derek Graham

Jie Lai

Peter H Manley

James Wihardja

Bengt J Borgstrom

Sandeep Kalra

Michael Tilelli

Paul Robert Bryson

Durai Thirupathi

Bryan Shaw

Nhan Tran

Avik Santra

Elias Nemer

Patrick Cruise

Russell S Ericksen

Ted Wada

Brett Harris

Daniele Giacobello

Kaiping Li

Aidan Smyth

Vikram Kumar Ramanna

Bret Harris

Niall Lyons

Rodolfo Gondim Lossio

Daniel Watson

Russel S Ericksen

Systems, methods, and devices detect audio signals. Methods may include receiving an audio input at an audio front end circuit, and identifying, using a first circuit, a wake word based, at least in part, on the received audio signal. Methods may also include determining if the identifying performed by the first circuit should be modified based, at least in part, on a designated threshold of accuracy associated with the first circuit and a result of the identifying, the designated threshold of accuracy being determined based, at least in part, on a language processing model of a second circuit. Moreover, the modifying may include adjusting wake word detection operations of the first circuit based, at least in part, on a result of the determining.

Systems, methods, and devices for wakeup word detection with continuous learning

Implementations disclosed describe methods, devices, and systems to perform out-of-distribution and recognition of activities using an inertial measurement unit (IMU) sensor. A method may include receiving motion data by a device from a motion sensor. The method further includes generating image data comprising one or more images based on the motion data. The method further includes determining that a first portion of the image data corresponds to activities outside a classification distribution. The method further includes filtering the image data by removing the first portion from the image and generating filtered image data. The method further includes determining an activity classification, within the classification distribution, based on the filtered image data. The method further includes modifying an operating parameter of the device based on the activity classification.

Out-of-distribution detection and recognition of activities with inertial measurement unit sensor

Systems, methods, and devices detect audio signals. Methods may include receiving an audio input at an audio front end circuit, starting, using a low power circuit, one or more buffers in response to receiving the audio input, and identifying, using the low power circuit, speech included in the audio input. Methods may also include identifying, using the low power circuit and a high performance circuit, a wake word based, at least in part, on the identified speech, the high performance circuit being configured to verify the wake word identified by the low power circuit.

Systems, methods, and devices for staged wakeup word detection

Implementations disclosed describe methods and systems to perform the methods of deploying and executing machine learning models on target-specific computational platforms. Optimization techniques include but are not limited to alignment of kernel operations with hardware instructions of a target processing device, reduction of kernel dimensions near boundaries of data, efficient reuse of a small number of memory components during neural network operations, run-time quantization of data and neural network parameters, and other methods.

Efficient optimization for neural network deployment and execution

This disclosure describes a conferencing device with beamforming and echo cancellation that includes: a microphone array that further comprises a plurality of microphones oriented to develop a corresponding plurality of microphone signals; a processor configured to execute the following steps: (1) performing a beamforming operation; (2) performing an acoustic echo cancellation operation; (3) post processing; (4) selecting one or more of the post processed signals for transmission to the far end where a signal selector uses the far end signal as information to inhibit the signal selector from changing the selection of the post processed signals while only the far end signal is active.

Conferencing device with beamforming and echo cancellation

Described are techniques for noise-robust and speaker-independent keyword spotting (KWS) in an input audio signal that contains keywords used to activate voice-based human-computer interactions. A KWS system may combine the latent representation generated by a denoising autoencoder (DAE) with audio features extracted from the audio signal using a machine learning approach. The DAE may be a discriminative DAE trained with a quadruplet loss metric learning approach to create a highly-separable latent representation of the audio signal in the audio input feature space. In one aspect, spectral characteristics of the audio signal such as Log-Mel features are combined with the latent representation generated by a quadruplet loss variational DAE (QVDQE) as input to a DNN KWS classifier. The KWS system improves keyword classification accuracy versus using extracted spectral features alone, non-discriminative DAE latent representations alone, or the extracted spectral features combined with the non-discriminative DAE latent representations in a KWS classifier.

Noise robust representations for keyword spotting systems

This disclosure describes a conferencing device with beamforming and echo cancellation that includes: a microphone array that further comprises a plurality of microphones oriented to develop a corresponding plurality of microphone signals; a processor configured to execute the following steps: (1) performing a beamforming operation to combine the plurality of microphone signals from the microphone array into a plurality of combined signals, (2) performing an acoustic echo cancellation operation on the plurality of combined signals to generate a plurality of combined echo cancelled signals, (3) receiving with a voice activity detector the far end signal as an input, (4) selecting one or more of the combined echo cancelled signals for transmission to the far end where a signal selector uses the far end signal as information to inhibit the signal selector from changing the selection of the combined echo cancelled signals while only the far end signal is active.

Described herein are devices, methods, and systems for detecting a phrase from uttered speech. A processing device may determine a first model for phrase recognition based on a likelihood ratio using a set of training utterances. The set of utterances may be analyzed by the first model to determine a second model, the second model comprising a training state sequence for each of the set of training utterances, and wherein each training state sequence indicates a likely state for each time interval of a corresponding training utterance. A determination of whether a detected utterance corresponds to the phrase may be based on a concatenation of the first model and the second model.

Two stage user customizable wake word detection

This disclosure describes an apparatus and method of an embodiment of an invention that is a conferencing device that includes a microphone array that further comprises a plurality of microphones; a processor configured to execute the following steps: performing a beamforming operation to combine the plurality of microphones into a plurality of combined signals that is greater in number than one and less in number than the plurality of microphone signals, each of the plurality of combined signals corresponding to a different fixed beam; wherein performing the beamforming operation includes applying beamforming weights to the signals from each microphone to achieve a desired pickup pattern that includes a main lobe and sidelobes together with nulls for each fixed beam; performing an acoustic echo cancellation operation generate a plurality of combined echo cancelled signals; and selecting one or more of the combined echo cancelled signals for transmission to the far end.

Conferencing device with microphone beamforming and echo cancellation

Example apparatus, systems and methods use a receiver of a first device to receive from a second device, radio frequency (RF) signals. Embodiments use a processor of the first device to determine, based on the RF signals, a set of angle-estimation values of an angle between a plurality of antenna elements of one of the first device and the second device and an antenna element of the other of the first device and the second device, and a set of confidence measurements. Each of the set of confidence measurements indicates a confidence of an angle-estimation value of the set of angle-estimation values.

Estimating angle measurements for source tracking using a phased array system

This disclosure describes an apparatus and method of an embodiment of an invention that is a conferencing apparatus. This embodiment of the apparatus/system includes a microphone array that further comprises a plurality of microphones where each microphone is configured to sense acoustic waves and the plurality of microphones are oriented to develop a corresponding plurality of microphone signals; a processor, memory, and storage operably coupled to the microphone array, the processor configured to: perform a beamforming operation; perform an acoustic echo cancellation operation; perform a direction of arrival determination; and select one or more of the combined echo cancelled signals.

Conferencing apparatus

Systems and methods provide a first sample of audio data and detect speech onset in the first sample of the audio data. Responsive to detecting the speech onset, systems and methods switch from capturing second samples of the audio data at first intervals, to capturing the second samples of the audio data at second intervals. Systems and methods provide contiguous audio data using the second samples of the audio data captured at the first intervals and at least one captured portion of the second samples of the audio data captured at the second intervals.

Systems and methods for capturing noise for pattern recognition processing

Techniques for non-linear acoustic echo cancellation are described herein. In an embodiment, a system comprises a loudspeaker, a microphone array, a spatial filtering logic with a spatial filter, an acoustic echo canceller (AEC) logic and an adder logic block. The spatial filtering logic is configured to generate a spatially-filtered signal by applying the spatial filter using a reference signal sent to the loudspeaker and a multi-channel microphone signal from the microphone array. The generated spatially-filtered signal carries both linear echo and non-linear echo that are included in the multi-channel microphone signal. The AEC logic is configured to apply a linear adaptive filter using the spatially-filtered signal to generate a cancellation signal that estimates both the linear echo and the non-linear echo of the multi-channel microphone signal. The adder logic block is configured to generate an output signal based on the cancellation signal.

Techniques for removing non-linear echo in acoustic echo cancellers

Techniques for acoustic echo cancellation are described herein. In an example embodiment, a system comprises a speaker, a microphone array with multiple microphones, a beamformer (BF) logic and an acoustic echo canceller (AEC) logic. The speaker is configured to receive a reference signal. The BF logic is configured to receive audio signals from the multiple microphones and to generate a beamformed signal. The AEC logic is configured to receive the beamformed signal and the reference signal. The AEC logic is also configured to compute a vector of bias coefficients multiple times per time frame, to compute a background filter coefficient based on the vector of bias coefficients, to apply a background filter to the reference signal and the beamformed signal based on the background filter coefficient, to generate a background cancellation signal, and to generate an output signal based at least on the background cancellation signal.

Beamformer and acoustic echo canceller (AEC) system

A method includes using a receiver of a first device, receiving from a second device, radio frequency (RF) signals. The method also includes using a processor of the first device, determining and storing, based on the RF signals, a set of angle-estimation values of an angle between a plurality of antenna elements of one of the first device and the second device and an antenna element of the other of the first device and the second device, a set of confidence measurements, and at least one of an Area-of Arrival (ARoA) value and an Area-of Departure (ARoD) value. Each of the set of confidence measurements indicates a confidence of an angle-estimation value of the set of angle-estimation values.

Growing community of inventors

Murray, UT, United States of America

Ashutosh Pandey