Analog Devices,inc.

Johannes Traa

Atulya Yellepeddi

Nicolas Le Dortz

David Wingate

Kaushal Sanghai

Hemtej Gullapalli

Noah Stein

Omer Tanovic

Erfan Soltanmohammadi

Brian C Donnelly

John Robert McCarty

Reuben Harry Cohn-gordon

Harshvardhan Bhatia

Jiayi Jiang

Sai Kulkarni

A device for proximity detection includes multiple electrodes and an impedance sensor coupled to the electrodes. The impedance sensor may include three impedance elements and a sensing element arranged in a bridge configuration to offset an external impedance and detect changes to impedance in the environment of the device. The device further includes a proximity detector that obtains sensor measurements between multiple subsets of electrodes and analyzes the sensor measurements to determine whether an object is approaching the device.

Front-facing proximity detection using capacitive sensor

Far field devices typically rely on audio only for enabling user interaction and involve only audio processing. Adding a vision-based modality can greatly improve the user interface of far field devices to make them more natural to the user. For instance, users can look at the device to interact with it rather than having to repeatedly utter a wakeword. Vision can also be used to assist audio processing, such as to improve the beamformer. For instance, vision can be used for direction of arrival estimation. Combining vision and audio can greatly enhance the user interface and performance of far field devices.

Multi-modal far field user interfaces and vision-assisted audio processing

The battery monitoring techniques described herein may be used for detection of battery anomalies or faults. Also, the battery monitoring techniques described herein may be used to generate estimates of total battery capacity. The battery monitoring techniques may employ an alternating current frequency response (ACFR) of the battery. The ACFR response of the battery may be used to detect anomalies and/or estimate a total capacity of the battery.

System and method for anomaly detection and total capacity estimation of a battery

An approach to processing of acoustic signals acquired at a user's device include one or both of acquisition of parallel signals from a set of closely spaced microphones, and use of a multi-tier computing approach in which some processing is performed at the user's device and further processing is performed at one or more server computers in communication with the user's device. The acquired signals are processed using time versus frequency estimates of both energy content as well as direction of arrival. In some examples, a non-negative matrix or tensor factorization approach is used to identify multiple sources each associated with a corresponding direction of arrival of a signal from that source. In some examples, data characterizing direction of arrival information is passed from the user's device to a server computer where direction-based processing is performed.

Time-frequency directional processing of audio signals

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Urbana, IL, United States of America

Johannes Traa