Google Inc.

Ulas Kirazci

Barnaby John James

Bo Wang

Adam Coimbra

Sunil Vemuri

Ilya Firman

Carey Radebaugh

Petar Aleksic

David Roy Schairer

Ertan Dogrultan

Gaurav Bhaya

Othar Hansson

Abraham Lee

Thushan Amarasiriwardena

Bradley M Abrams

Anton Hansson

Wei Dong

Steve Chen

Valerie Nygaard

Jason Brant Douglas

Luv Kothari

Scott Banachowski

David T Wang

Joshua Richard Williams

Justin Foutts

Anna Lynn Patterson

Ankit K Jain

Tania Bedrax-Weiss

Brendan D Burns

Abhishek Das

Yudong Sun

Geza Kovacs

Xiao Gao

Methods, systems, and apparatus, for automatically generating search suggestions based on history data for multiple native application on a user device.

Search suggestions based on native application history

Systems and methods of invoking functions of agents via digital assistant applications are provided. Each action-inventory can have an address template for an action by an agent. The address template can include a portion having an input variable used to execute the action. A data processing system can parse an input audio signal from a client device to identify a request and a parameter to be executed by the agent. The data processing system can select an action-inventory for the action corresponding to the request. The data processing system can generate, using the address template, an address. The address can include a substring having the parameter used to control execution of the action. The data processing system can direct an action data structure including the address to the agent to cause the agent to execute the action and to provide output for presentation.

Invoking functions of agents via digital assistant applications using address templates

Implementations relate to dynamically, and in a context-sensitive manner, biasing voice to text conversion. In some implementations, the biasing of voice to text conversions is performed by a voice to text engine of a local agent, and the biasing is based at least in part on content provided to the local agent by a third-party (3P) agent that is in network communication with the local agent. In some of those implementations, the content includes contextual parameters that are provided by the 3P agent in combination with responsive content generated by the 3P agent during a dialog that: is between the 3P agent, and a user of a voice-enabled electronic device; and is facilitated by the local agent. The contextual parameters indicate potential feature(s) of further voice input that is to be provided in response to the responsive content generated by the 3P agent.

Voice to text conversion based on third-party agent content

Techniques are described herein for multi-modal interaction between users, automated assistants, and other computing services. In various implementations, a user may engage with the automated assistant in order to further engage with a third party computing service. In some implementations, the user may advance through dialog state machines associated with third party computing service using both verbal input modalities and input modalities other than verbal modalities, such as visual/tactile modalities.

Multi-modal interaction between users, automated assistants, and other computing services

The present disclosure is generally directed to the generation of voice-activated data flows in interconnected network. The voice-activated data flows can include input audio signals that include a request and are detected at a client device. The client device can transmit the input audio signal to a data processing system, where the input audio signal can be parsed and passed to the data processing system of a service provider to fulfill the request in the input audio signal. The present solution is configured to conserve network resources by reducing the number of network transmissions needed to fulfill a request.

Activation of remote devices in a networked system

Some implementations are directed to selective invocation of a particular third-party (3P) agent by an automated assistant to achieve an intended action determined by the automated assistant during a dynamic dialog between the automated assistant and a user. In some of those implementations, the particular 3P agent is invoked with value(s) for parameter(s) that are determined during the dynamic dialog; and/or the particular 3P agent is selected, from a plurality of candidate 3P agents, for invocation based on the determined value(s) for the parameter(s) and/or based on other criteria. In some of those implementations, the automated assistant invokes the particular 3P agent by transmitting, to the particular 3P agent, a 3P invocation request that includes the determined value(s) for the parameter(s).

Generating and transmitting invocation request to appropriate third-party agent

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for facilitating input by a user into a form. In one aspect, a method include actions of obtaining a web resource that includes a form, determining a particular field of the form has been selected, determining an intent that corresponds to the form from a first semantic tag in the web resource, determining a parameter of the intent that corresponds to the particular field of the form from a second semantic tag in the web resource, determining a value to suggest for the particular field based at least on the intent and the parameter of the intent, and providing the value for output as a suggestion of input for the particular field.

Input facilitation for forms in web resources

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Mountain View, CA, United States of America

Ulas Kirazci