USER INTERFACE FOR CORRECTING RECOGNITION ERRORS

    公开(公告)号:US20190318739A1

    公开(公告)日:2019-10-17

    申请号:US16412137

    申请日:2019-05-14

    Applicant: Apple Inc.

    Abstract: Speech recognition is performed on a received utterance to determine a plurality of candidate text representations of the utterance, including a primary text representation and one or more alternative text representations. Natural language processing is performed on the primary text representation to determine a plurality of candidate actionable intents, including a primary actionable intent and one or more alternative actionable intents. A result is determined based on the primary actionable intent. The result is provided to the user. A recognition correction trigger is detected. In response to detecting the recognition correction trigger, a set of alternative intent affordances and a set of alternative text affordances are concurrently displayed.

    METHOD FOR EXTRACTING SALIENT DIALOG USAGE FROM LIVE DATA

    公开(公告)号:US20190034040A1

    公开(公告)日:2019-01-31

    申请号:US16144871

    申请日:2018-09-27

    Applicant: Apple Inc.

    Abstract: Systems and processes are disclosed for virtual assistant request recognition using live usage data and data relating to future events. User requests that are received but not recognized can be used to generate candidate request templates. A count can be associated with each candidate request template and can be incremented each time a matching candidate request template is received. When a count reaches a threshold level, the corresponding candidate request template can be used to train a virtual assistant to recognize and respond to similar user requests in the future. In addition, data relating to future events can be mined to extract relevant information that can be used to populate both recognized user request templates and candidate user request templates. Populated user request templates (e.g., whole expected utterances) can then be used to recognize user requests and disambiguate user intent as future events become relevant.

    METHOD FOR EXTRACTING SALIENT DIALOG USAGE FROM LIVE DATA
    5.
    发明申请
    METHOD FOR EXTRACTING SALIENT DIALOG USAGE FROM LIVE DATA 审中-公开
    从实时数据中提取真实对话框的方法

    公开(公告)号:US20150161521A1

    公开(公告)日:2015-06-11

    申请号:US14099776

    申请日:2013-12-06

    Applicant: APPLE INC.

    CPC classification number: G06F3/0481 G06F17/278

    Abstract: Systems and processes are disclosed for virtual assistant request recognition using live usage data and data relating to future events. User requests that are received but not recognized can be used to generate candidate request templates. A count can be associated with each candidate request template and can be incremented each time a matching candidate request template is received. When a count reaches a threshold level, the corresponding candidate request template can be used to train a virtual assistant to recognize and respond to similar user requests in the future. In addition, data relating to future events can be mined to extract relevant information that can be used to populate both recognized user request templates and candidate user request templates. Populated user request templates (e.g., whole expected utterances) can then be used to recognize user requests and disambiguate user intent as future events become relevant.

    Abstract translation: 公开了使用实时使用数据和与未来事件相关的数据的虚拟助理请求识别的系统和过程。 接收但未识别的用户请求可用于生成候选请求模板。 计数可以与每个候选请求模板相关联,并且可以在每次接收到匹配的候选请求模板时递增计数。 当计数达到阈值水平时,可以使用相应的候选请求模板来训练虚拟助理以识别和响应将来的类似用户请求。 另外,与未来事件有关的数据也可以被挖掘出来,以提取可用于填充认可用户请求模板和候选用户请求模板的相关信息。 然后可以使用填充的用户请求模板(例如,整个预期的话语)来识别用户请求,并在未来的事件变得相关时消除用户意图。

    METHOD FOR EXTRACTING SALIENT DIALOG USAGE FROM LIVE DATA

    公开(公告)号:US20220214775A1

    公开(公告)日:2022-07-07

    申请号:US17703308

    申请日:2022-03-24

    Applicant: Apple Inc.

    Abstract: Systems and processes are disclosed for virtual assistant request recognition using live usage data and data relating to future events. User requests that are received but not recognized can be used to generate candidate request templates. A count can be associated with each candidate request template and can be incremented each time a matching candidate request template is received. When a count reaches a threshold level, the corresponding candidate request template can be used to train a virtual assistant to recognize and respond to similar user requests in the future. In addition, data relating to future events can be mined to extract relevant information that can be used to populate both recognized user request templates and candidate user request templates. Populated user request templates (e.g., whole expected utterances) can then be used to recognize user requests and disambiguate user intent as future events become relevant.

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