Facebook, Inc.

Meta Platforms, Inc.

Michael Robert Hanson

Emmanouil Koukoumidis

Benoit F Dumoulin

Rajen Subba

Mohsen M Agsen

Heidi Young

Jinsong Yu

Chandrasekhar Iyer

Fuchun Peng

Rushin N Shah

Jeremy Gillmor Kahn

Xiaohu Liu

Jiedan Zhu

Wenhai Yang

Anuj Kumar

Kun Han

Charles Jolley

Lloyd Hilaiel

Fei Sha

David Baggeroer

Gary Eugene Baalman

Rachel Jordan Engel

In one embodiment, a method includes receiving a user query inputted on a head-mounted device from the head-mounted device, wherein the user query corresponds to multiple dialog-intents, executing multiple tasks corresponding to the multiple dialog-intents, generating a multi-perspective response by a stitching model based on two or more of execution results of the multiple tasks, wherein the stitching model combines the two or more of the execution results based on natural language processing, and wherein the multi-perspective response comprises a natural-language response combining the two or more execution results, and sending instructions to the head-mounted device for presenting the multi-perspective response on the head-mounted device.

Generating multi-perspective responses by assistant systems

In one embodiment, a method includes receiving a first user input from a first user, wherein the first user input comprises a partial request, presenting one or more suggested intent auto-completions corresponding to the partial request, receiving a selection by the first user of a first suggested intent auto-completion of the suggested intent auto-completions and a second user input, presenting one or more suggested slot auto-completions corresponding to one or more candidate slot-hypotheses corresponding to the second user input, respectively, wherein each of the candidate slot-hypotheses comprise a slot-suggestion, and wherein each suggested slot auto-completion comprises the second user input and the corresponding candidate slot-hypothesis, receiving a selection by the first user of a first suggested slot auto-completion of the suggested slot auto-completions, and presenting execution results of one or more tasks corresponding to the first suggested intent auto-completion and the first suggested slot auto-completion.

Contextual auto-completion for assistant systems

In one embodiment, a method includes receiving a user query associated with dialog-intents at a client system, executing tasks corresponding to the dialog-intents, generating a multi-perspective response by a stitching model based on two or more of execution results of the tasks, wherein the multi-perspective response comprises a natural-language response combining the two or more execution results, and presenting the multi-perspective response at the client system.

In one embodiment, a method includes, by a client system, receiving, at the client system, a first user input, processing by the client system, the first user input to provide an initial response by identifying one or more entities referenced by the first user input and providing, by the client system, the initial response, where the initial response includes a conversational filler referencing at least one of the one or more identified entities, processing the first user input to provide a complete response by identifying, by the client system, one or more intents and one or more slots associated with the first user input based on a semantic analysis by a natural-language understanding module, and providing, by the client system, the complete response subsequent to the initial response, where the complete response is based on the one or more intents and the one or more slots.

Predictive injection of conversation fillers for assistant systems

In one embodiment, a method includes receiving a user query from a client system associated with a first user, determining a plurality of dialog-intents, each being associated with a particular agent of a plurality of agents, executing a plurality of tasks corresponding to the user query via the plurality of agents corresponding to the plurality of dialog-intents, receiving a plurality of execution results corresponding to the plurality of tasks from the plurality of agents, respectively, selecting two or more of the plurality of execution results for combination, generating a multi-perspective response based on the selected execution results by a stitching model, wherein the multi-perspective response comprises a natural-language response combining the selected execution results, and sending instructions for presenting the multi-perspective response to the first user to the client system in response to the user query.

In one embodiment, a method includes, by one or more computing systems, receiving, from a client system associated with a first user, a first user input from the first user, identifying one or more entities referenced by the first user input, determining a classification of the first user input based on a machine-learning classifier model, generating several candidate conversational fillers based on the classification of the first user input and the one or more identified entities, wherein each candidate conversational filler references at least one of the one or more identified entities, ranking the candidate conversational fillers based on a relevancy of the candidate conversational filler to the first user input and a decay model hysteresis, and sending instructions for presenting a top-ranked candidate conversational filler as an initial response to the first user.

In one embodiment, a method includes receiving a first audio input from a user requesting access to information or a service, sending a request for the information or service to an authentication server, where the request includes first authentication information based on the first audio input and further includes a user identifier associated with the user, receiving a second audio input from a client system of the user, where the second audio input includes a first authentication code to be compared to a second authentication code generated by the authentication server, sending second authentication information based on the second audio input and the user identifier to the authentication server for verification, receiving, from the authentication server, an indication of whether the user is successfully authenticated based on the second authentication information, and providing, to the user, access to the information or service when the user is successfully authenticated.

Secure authentication for assistant systems

In one embodiment, a method includes, by one or more computing systems, receiving, from a client system associated with a user, an initial portion of a user input, wherein the initial portion comprises a partial request, and wherein the initial portion is received while the user is continuing to provide further input, generating, responsive to receiving the initial portion of the user input, one or more speculative queries based on the partial request and a machine-learning predictive model, wherein each speculative query is a predicted complete request based on the partial request, calculating a confidence score for each speculative query based on the predictive model, ranking the one or more speculative queries based on their respective confidence scores and associated costs, executing one or more of the speculative queries based on their ranks, and caching one or more results of the executed one or more speculative queries.

Context-based utterance prediction for assistant systems

In one embodiment, a method includes receiving a user request for a summarization of a particular type of content objects from a client system associated with a first user, determining one or more modalities associated with the user request, selecting a plurality of content objects of the particular type based on a user profile of the first user, wherein the user profile comprises one or more confidence scores associated with one or more subjects associated with the first user, respectively, and wherein the plurality of content objects are selected based on the one or more confidence scores, generating a summary of each content object based on the user profile and the determined modalities, and sending, to the client system in response to the user request, instructions for presenting the summaries of the plurality of content objects, wherein the summaries are presented via one or more of the determined modalities.

Generating personalized content summaries for users

In one embodiment, a method includes receiving a user input including a partial request from a client system of a first user, analyzing the user input to generate one or more candidate hypotheses based on a personalized language model where each of the candidate hypotheses includes one or more of an intent-suggestion or a slot-suggestion, sending instructions for presenting one or more suggested auto-completions corresponding to one or more of the candidate hypotheses, respectively, to the client system, where each suggested auto-completion comprises the partial request and the corresponding candidate hypothesis, receiving an indication of a selection by the first user of a first suggested auto-completion of the suggested auto-completions from the client system, and executing one or more tasks based on the first suggested auto-completion selected by the first user via one or more agents.

A set of search results associated with a query is received, the set of search results including for each of search result in at least a subset of the set an indication of an evidence based at least in part on which the search result was included in the set of search results. A search result display interface is generated in which at least a displayed subset of search results are displayed, the search result display interface include for each of at least a subset of the displayed search results an indication of the corresponding evidence based on which that search result was included in the set of search results.

Growing community of inventors

Los Altos, CA, United States of America

Michael Robert Hanson