Contextual Auto-Completion for Assistant Systems

    公开(公告)号:US20190324780A1

    公开(公告)日:2019-10-24

    申请号:US16150069

    申请日:2018-10-02

    Applicant: Facebook, Inc.

    Abstract: 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.

    Secure authentication for assistant systems

    公开(公告)号:US11115410B1

    公开(公告)日:2021-09-07

    申请号:US16182542

    申请日:2018-11-06

    Applicant: Facebook, Inc.

    Abstract: 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.

    Predictive injection of conversation fillers for assistant systems

    公开(公告)号:US11245646B1

    公开(公告)日:2022-02-08

    申请号:US16192538

    申请日:2018-11-15

    Applicant: Facebook, Inc.

    Abstract: 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.

    Context-based utterance prediction for assistant systems

    公开(公告)号:US11086858B1

    公开(公告)日:2021-08-10

    申请号:US16222957

    申请日:2018-12-17

    Applicant: Facebook, Inc.

    Abstract: 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.

    Generating Personalized Content Summaries for Users

    公开(公告)号:US20190325084A1

    公开(公告)日:2019-10-24

    申请号:US15967290

    申请日:2018-04-30

    Applicant: Facebook, Inc.

    Abstract: 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.

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