Google Inc.

Lucia Terrenghi

Behshad Behzadi

Zaheed Sabur

Jonathan David Lee

Lucas Mirelmann

Daniel Cotting

Denis Burakov

Sergey Nazarov

Michael Golikov

Adrian Zumbrunnen

Steve Cheng

Mario Bertschler

Bohdan Vlasyuk

Yariv Adan

Robert Allen Ryskamp

Patrick Pui Wah Leung

Iyad F I Assad

Steve Anthony Rogers

Ammar Ibrahim

Pascal Corpet

Andrew John McGlinchey

Jannine C Versi

Implementations can reduce the time required to obtain responses from an automated assistant by, for example, obviating the need to provide an explicit invocation to the automated assistant, such as by saying a hot-word/phrase or performing a specific user input, prior to speaking a command or query. In addition, the automated assistant can optionally receive, understand, and/or respond to the command or query without communicating with a server, thereby further reducing the time in which a response can be provided. Implementations only selectively initiate on-device speech recognition responsive to determining one or more condition(s) are satisfied. Further, in some implementations, on-device NLU, on-device fulfillment, and/or resulting execution occur only responsive to determining, based on recognized text form the on-device speech recognition, that such further processing should occur. Thus, through selective activation of on-device speech processing, and/or selective activation of on-device NLU and/or on-device fulfillment, various client device resources are conserved.

Selectively activating on-device speech recognition, and using recognized text in selectively activating on-device NLU and/or on-device fulfillment

Implementations set forth herein relate to an automated assistant that can be invoked while a user is interfacing with a foreground application in order to retrieve data from one or more different applications, and then provide the retrieved data to the foreground application. A user can invoke the automated assistant while operating the foreground application by providing a spoken utterance, and the automated assistant can select one or more other applications to query based on content of the spoken utterance. Application data collected by the automated assistant from the one or more other applications can then be used to provide an input to the foreground application. In this way, the user can bypass switching between applications in the foreground in order to retrieve data that has been generated by other applications.

Automated assistant for generating, in response to a request from a user, application input content using application data from other sources

Various aspects of the subject technology relate to systems, methods, and machine-readable media for updating a point of interest (POI) data repository. A system may be configured to receive a communication comprising an image associated with a point of interest, extract textual data from the image, identify a portion of the textual data that corresponds to a point of interest (POI) field in a point of interest listing, and update the point of interest (POI) data repository based on the portion of the textual data that corresponds to the POI field.

Updating point of interest data based on an image

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Adliswil, Switzerland

Lucia Terrenghi