Google Inc.

Other

Rajeev Conrad Nongpiur

Michael D Dixon

James Edward Stewart

Chanwoo Kim

Jeffrey Alan Boyd

Seungho Yang

Christopher Charles Burns

Yu-An Lien

Rengarajan Aravamudhan

Sahana Mysore

Sayed Yusef Shafi

Hae Rim Jeong

Patrick M Lister

Chi Yeung Jonathan Ng

Jessica Yuan

Ananya Misra

Yoky Matsuoka

Tara N Sainath

Dongeek Shin

Jason Evans Goulden

Michiel A U Bacchiani

Arun Narayanan

Brian Mitchell Silverstein

Qian Zhang

Michiel Bacchiani

Khe Chai Sim

Lu Gao

Wei Li

Marco Tagliasacchi

Sze Chie Lim

Neil Zeghidour

Byungchul Kim

Vijayaditya Peddinti

Haerim Jeong

Leonardo Kusumo

Jian Guo

James Paul Tobin

Hélène Bahu

Michael Takezo Chinen

Jihan Li

Andrew James Sutter

Marie Vachovsky

Monica Song

Kung-Wei Liu

Chan Woo Kim

Jennifer Yeelam Wong

Andrew Christopher Felch

The technology generally relates to spatial audio communication between devices. For example, a first device and a second device may be connected via a communication link. The first device may capture audio signals in an environment through two or more microphones. The first device may encode the captured audio with spatial configuration data. The first device may transmit the encoded audio via the communication link to the second device. The second device may decode the encoded audio into binaural or ambisonic audio to be output by one or more speakers of the second device. The binaural or ambisonic audio may be converted into spatial audio to be output. The second device may output the binaural or spatial audio to create an immersive listening experience.

Spatial audio recording from home assistant devices

A method of detecting and responding to a visitor to a smart home environment via an electronic greeting system of the smart home environment, including determining that a visitor is approaching an entryway of the smart home environment; initiating a facial recognition operation while the visitor is approaching the entryway; initiating an observation window in response to the determination that a visitor is approaching the entryway; obtaining context information from one or more sensors of the smart home environment during the observation window; and at the end of the time window, initiating a response to the detected approach of the visitor based on the context information and/or an outcome of the facial recognition operation.

Systems and methods of detecting and responding to a visitor to a smart home environment

Various arrangements are detailed herein related to managing video recording based on spoken commands. A system receives a video stream from a video camera and analyzes a field of view in the received video stream to determine a location for one or more identified or potential users. The system can beamform audio from microphones of a home assistant device based on the location of the one or more identified or potential users. The system adjusts an audio output based on the location of the one or more identified or potential users, receives a spoken command from the one or more identified or potential users, and outputs a response to the spoken command.

Video integration with home assistant

Systems and techniques are provided for sound model localization within an environment. Sound recordings of sounds in the environment may be received from devices in the environment. Preliminary labels for the sound recordings may be determined using pre-trained sound models. The preliminary labels may have associated probabilities. Sound clips with preliminary labels may be generated based on sound recordings that have preliminary labels whose probability is over a high-recall threshold for the pre-trained sound model that determined the preliminary label. The sound clips with preliminary labels may be sent to a user device. Labeled sound clips may be received from the user device. The labeled sound clips may be based on the sound clips with preliminary labels. Training data sets may be generated for the pre-trained sound models using the labeled sound clips. The pre-trained sound models may be trained using the training data sets to generate localized sound models.

Sound model localization within an environment

A method for auralizing a multi-microphone device. Path information for one or more sound paths using dimensions and room reflection coefficients of a simulated room for one of a plurality of microphones included in a multi-microphone device is determined. An array-related transfer functions (ARTFs) for the one of the plurality of microphones is retrieved. The auralized impulse response for the one of the plurality of microphones is generated based at least on the retrieved ARTFs and the determined path information.

Auralization for multi-microphone devices

Methods, devices, systems, and means for video integration with a home assistant device are described herein. The home assistant device interacts with a person in a video stream by capturing, using a network-enabled outdoor video camera, a video stream of an outdoor location of a premises at which the person is present and analyzing the person appearing in the captured video stream to determine an identity of the person. Based on determining the identity of the person, the home assistant device announces a presence of the person that is outdoors and outputs instructions to the person.

A method of presenting appropriate actions for responding to a visitor to a smart home environment via an electronic greeting system of the smart home environment, including detecting a visitor of the smart home environment; obtaining context information from the smart home environment regarding the visitor; based on the context information, identifying a plurality of appropriate actions available to a user of a client device for interacting with the visitor via the electronic greeting system; and causing the identified actions to be presented to the user of the client device.

Systems and methods of presenting appropriate actions for responding to a visitor to a smart home environment

Systems and methods are described for improving endpoint detection of a voice query submitted by a user. In some implementations, a synchronized video data and audio data is received. A sequence of frames of the video data that includes images corresponding to lip movement on a face is determined. The audio data is endpointed based on first audio data that corresponds to a first frame of the sequence of frames and second audio data that corresponds to a last frame of the sequence of frames. A transcription of the endpointed audio data is generated by an automated speech recognizer. The generated transcription is then provided for output.

Query endpointing based on lip detection

Various arrangements are detailed herein related to managing video recording. A system can include a network-enabled video camera that captures a video stream of a location and streams the video stream to a cloud-based home assistant integration platform. The system can include a home assistant device comprising a microphone and wireless network interface, the home assistant device configured to receive, via the microphone, a spoken command that requests video, captured by the network-enabled video camera, be recorded. The cloud-based home assistant integration platform may be configured to analyze the video stream captured using the network-enabled video camera to determine an identity of the user. The platform may be further configured to store a portion of the video stream linked to a user account of the user based on the spoken command and the identity of the user.

Various arrangements are detailed herein related to modifying a shopping list using a home assistant device and an integrated video service. A network-enabled video camera may be used to capture a video stream of a location at which a user is present. A home assistant device may receive a spoken command that requests an item be added to a shopping list. The video stream captured using the network-enabled video camera may be analyzed to determine an identity of the user. A shopping list to modify may be determined based on the identity of the user. The determined shopping list may then be modified to indicate the item requested in the spoken command.

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Palo Alto, CA, United States of America

Rajeev Conrad Nongpiur