Data driven natural language event detection and classification

    公开(公告)号:AU2017203783B2

    公开(公告)日:2018-04-05

    申请号:AU2017203783

    申请日:2017-06-05

    Applicant: APPLE INC

    Abstract: Systems and processes for operating a digital assistant are provided. In accordance with one or more examples, a method includes, at a user device with one or more processors and memory, receiving unstructured natural language information from at least one user. The method also includes, in response to receiving the unstructured natural language information, determining whether event information is present in the unstructured natural language information. The method further includes, in accordance with a determination that event information is present within the unstructured natural language information, determining whether an agreement on an event is present in the unstructured natural language information. The method further includes, in accordance with a determination that an agreement on an event is present, determining an event type of the event and providing an event description based on the event type. 13 of 42 Unstructured Natural Language Event Information Detection Module Event Agreement Detection Module Event Type Determination Module Digital Assistant Event Description Generation Module 'I Event Description

    Multi-command single utterance input method

    公开(公告)号:AU2015266863A1

    公开(公告)日:2016-09-29

    申请号:AU2015266863

    申请日:2015-05-28

    Applicant: APPLE INC

    Abstract: Systems and processes are disclosed for handling a multi-part voice command for a virtual assistant. Speech input can be received from a user that includes multiple actionable commands within a single utterance. A text string can be generated from the speech input using a speech transcription process. The text string can be parsed into multiple candidate substrings based on domain keywords, imperative verbs, predetermined substring lengths, or the like. For each candidate substring, a probability can be determined indicating whether the candidate substring corresponds to an actionable command. Such probabilities can be determined based on semantic coherence, similarity to user request templates, querying services to determine manageability, or the like. If the probabilities exceed a threshold, the user intent of each substring can be determined, processes associated with the user intents can be executed, and an acknowledgment can be provided to the user.

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