Providing a personal assistant module with a selectively-traversable state machine

    公开(公告)号:US10462619B2

    公开(公告)日:2019-10-29

    申请号:US15177327

    申请日:2016-06-08

    Applicant: Google Inc.

    Abstract: Techniques are described herein for leveraging an online semantic processor to generate a finite state machine to be delivered to and implemented on a resource-constrained device. In various implementations, a user request may be received by a personal assistant module. Data indicative of the user request may be uploaded, e.g., by the personal assistant module, to an online semantic processor. Data may be received, e.g., by the personal assistant module, from the online semantic processor. The received data may represent a state machine having a plurality of candidate states of the personal assistant module. Each candidate state may be potentially responsive to the request. Resources local to the resource-constrained device may be analyzed to ascertain signal(s) unavailable to the online semantic processor. The personal assistant module may then transition to a given state of the plurality of candidate states. The given state may be selected based on the signal(s).

    PROVIDING A PERSONAL ASSISTANT MODULE WITH A SELECTIVELY-TRAVERSABLE STATE MACHINE

    公开(公告)号:US20170359707A1

    公开(公告)日:2017-12-14

    申请号:US15177327

    申请日:2016-06-08

    Applicant: Google Inc.

    Abstract: Techniques are described herein for leveraging an online semantic processor to generate a finite state machine to be delivered to and implemented on a resource-constrained device. In various implementations, a user request may be received by a personal assistant module. Data indicative of the user request may be uploaded, e.g., by the personal assistant module, to an online semantic processor. Data may be received, e.g., by the personal assistant module, from the online semantic processor. The received data may represent a state machine having a plurality of candidate states of the personal assistant module. Each candidate state may be potentially responsive to the request. Resources local to the resource-constrained device may be analyzed to ascertain signal(s) unavailable to the online semantic processor. The personal assistant module may then transition to a given state of the plurality of candidate states. The given state may be selected based on the signal(s).

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