Google Inc.

Gray Ice Higdon

Zaheed Sabur

Behshad Behzadi

Lucas Mirelmann

Denis Burakov

Steve Cheng

Andrea Terwisscha Van Scheltinga

Daniel Cotting

Sergey Nazarov

Michael Golikov

Bohdan Vlasyuk

Mario Bertschler

Tilke Mary Judd

Luv Kothari

Dhruv Bakshi

Ibrahim Badr

Adrian Zumbrunnen

Alexandru Ovidiu Dovlecel

Ardan Arac

Jan Lamecki

Nicolo D'Ercole

Koa Metter

Michael Vladimirovich Reutov

Quentin Lascombes De Laroussilhe

Vladyslav Lysychkin

Mikhail Golikov

Pratik Gilda

Eduardo Jodas Samper

Bryan Christopher Horling

Vladimir Vuskovic

Yariv Adan

Mikhail Reutov

Lan Huo

Alvin Abdagic

Victor Carbune

Marcin M Nowak-Przygodzki

Jyrki Antero Alakuijala

Jonathan David Lee

Okan Kolak

Megan Knight

Vinh Quoc Ly

Mugurel Ionut Andreica

Yan Zhong

Fredrik Bergenlid

Bibo Xu

Julia Proskurnia

Radu Voroneanu

Jacopo Sannazzaro Natta

Peter W Dickman

Lucia Terrenghi

Abraham Moolenaar

Marvin Chow

Marie Patriarche Bledowski

Srikanth Pandiri

Yang Lu

Xu Liu

Gokay Baris Gultekin

Angana Ghosh

Akshay Kannan

Bo Zhang

Domenico Carbotta

Justin Lu

Qi Wang

Krishna Sapkota

Magali Boizot-Roche

Márius Sajgalík

Nicholas Fey

Viesturs Zarins

Krzysztof Andrzej Goj

Nicholas G Fey

Implementations include actions of obtaining a set of entities based on one or more terms of a query, obtaining one or more entities associated with each live event of a plurality of live events, identifying a live event that is responsive to the query based on comparing at least one entity in the set of entities to one or more entities associated with each live event of a plurality of live events, determining that an event search result corresponding to the live event is to be displayed in search results, and in response: providing the event search result for display, the event search result including information associated with the live event, the information including an indicator of an occurrence of the live event.

Surfacing live events in search results

Implementations set forth herein relate to a system that employs an automated assistant to further interactions between a user and another application, which can provide the automated assistant with permission to initialize relevant application actions simultaneous to the user interacting with the other application. Furthermore, the system can allow the automated assistant to initialize actions of different applications, despite being actively operating a particular application. Available actions can be gleaned by the automated assistant using various application-specific schemas, which can be compared with incoming requests from a user to the automated assistant. Additional data, such as context and historical interactions, can also be used to rank and identify a suitable application action to be initialized via the automated assistant.

Initializing non-assistant background actions, via an automated assistant, while accessing a non-assistant application

Implementations described herein relate to an application and/or automated assistant that can identify arrangement operations to perform for arranging text during speech-to-text operations—without a user having to expressly identify the arrangement operations. In some instances, a user that is dictating a document (e.g., an email, a text message, etc.) can provide a spoken utterance to an application in order to incorporate textual content. However, in some of these instances, certain corresponding arrangements are needed for the textual content in the document. The textual content that is derived from the spoken utterance can be arranged by the application based on an intent, vocalization features, and/or contextual features associated with the spoken utterance and/or a type of the application associated with the document, without the user expressly identifying the corresponding arrangements. In this way, the application can infer content arrangement operations from a spoken utterance that only specifies the textual content.

Arranging and/or clearing speech-to-text content without a user providing express instructions

Implementations relate to providing information items for display during a communication session. In some implementations, a computer-implemented method includes receiving, during a communication session between a first computing device and a second computing device, first media content from the communication session. The method further includes determining a first information item for display in the communication session based at least in part on the first media content. The method further includes sending a first command to at least one of the first computing device and the second computing device to display the first information item.

Assistance during audio and video calls

A first computing device may receive an indication of user input that is at least a part of a conversation between a user and a first assistant executing at the first computing device. The first assistant and/or an assistant executing at a digital assistant system may determine whether to handoff the conversation from the first assistant executing at the first computing device to a second assistant executing at a second computing device. In response to determining to handoff the conversation to the second assistant executing at the second computing device, the first assistant and/or the assistant executing at the digital assistant system may send to the second computing device a request to handoff the conversation which includes at least an indication of the conversation.

Cross-device handoffs

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

Determining whether, upon cessation of a second automated assistant session that interrupted and supplanted a prior first automated assistant session: (1) to automatically resume the prior first automated assistant session, or (2) to transition to an alternative automated assistant state in which the prior first session is not automatically resumed. Implementations further relate to selectively causing, based on the determining and upon cessation of the second automated assistant session, either the automatic resumption of the prior first automated assistant session that was interrupted, or the transition to the state in which the first session is not automatically resumed.

Determining whether to automatically resume first automated assistant session upon cessation of interrupting second session

Implementations can reduce the time required to obtain responses from an automated assistant through proactive caching, locally at a client device, of proactive assistant cache entries—and through on-device utilization of the proactive assistant cache entries. Different proactive cache entries can be provided to different client devices, and various implementations relate to technique(s) utilized in determining which proactive cache entries to provide to which client devices. In some of those implementations, in determining which proactive cache entries to provide (proactively or in response to a request) to a given client device, a remote system selects, from a superset of candidate proactive cache entries, a subset of the cache entries for providing to the given client device.

Proactive caching of assistant action content to enable resolution of spoken or typed utterances

Methods, apparatus, and computer readable media are described related to automated assistants that proactively incorporate, into human-to-computer dialog sessions, unsolicited content of potential interest to a user. In various implementations, in an existing human-to-computer dialog session between a user and an automated assistant, it may be determined that the automated assistant has responded to all natural language input received from the user. Based on characteristic(s) of the user, information of potential interest to the user or action(s) of potential interest to the user may be identified. Unsolicited content indicative of the information of potential interest to the user or the action(s) may be generated and incorporated by the automated assistant into the existing human-to-computer dialog session. In various implementations, the incorporating may be performed in response to the determining that the automated assistant has responded to all natural language input received from the user during the human-to-computer dialog session.

Proactive incorporation of unsolicited content into human-to-computer dialogs

Systems and methods described herein relate to determining whether to incorporate recognized text, that corresponds to a spoken utterance of a user of a client device, into a transcription displayed at the client device, or to cause an assistant command, that is associated with the transcription and that is based on the recognized text, to be performed by an automated assistant implemented by the client device. The spoken utterance is received during a dictation session between the user and the automated assistant. Implementations can process, using automatic speech recognition model(s), audio data that captures the spoken utterance to generate the recognized text. Further, implementations can determine whether to incorporate the recognized text into the transcription or cause the assistant command to be performed based on touch input being directed to the transcription, a state of the transcription, and/or audio-based characteristic(s) of the spoken utterance.

Voice commands for an automated assistant utilized in smart dictation

Implementations set forth herein relate to an automated assistant that can selectively determine whether to incorporate a verbatim interpretation of portions spoken utterances into an entry field and/or incorporate synonymous content into the entry field. For instance, a user can be accessing an interface that provides an entry field (e.g., address field) for receiving user input. In order to provide input for entry field, the user can select the entry field and/or access a GUI keyboard to initialize an automated assistant for assisting with filling the entry field. Should the user provide a spoken utterance, the user can elect to provide a spoken utterance that embodies the intended input (e.g., an actual address) or a reference to the intended input (e.g., a name). In response to the spoken utterance, the automated assistant can fill the entry field with the intended input without necessitating further input from the user.

Voice-controlled entry of content into graphical user interfaces

Implementations set forth herein allow a user to access a first application in a foreground of a graphical interface, and simultaneously employ an automated assistant to respond to notifications arising from a second application. The user can provide an input, such as a spoken utterance, while viewing the first application in the foreground in order to respond to notifications from the second application without performing certain intervening steps that can arise under certain circumstances. Such intervening steps can include providing a user confirmation, which can be bypassed, and/or time-limited according to a timer, which can be displayed in response to the user providing a responsive input directed at the notification. A period for the timer can be set according to one or more characteristics that are associated with the notification, the user, and/or any other information that can be associated with the user receiving the notification.

Dynamically delaying execution of automated assistant actions and/or background application requests

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Adliswil, Switzerland

Zaheed Sabur