METHODS FOR NATURAL LANGUAGE MODEL TRAINING IN NATURAL LANGUAGE UNDERSTANDING (NLU) SYSTEMS

    公开(公告)号:US20210271816A1

    公开(公告)日:2021-09-02

    申请号:US16805307

    申请日:2020-02-28

    Abstract: Systems and methods for training a natural language model of a natural language understanding (NLU) system are disclosed herein. A text string including at least a content entity is received. A determination is made as to whether the text string includes an obsequious expression. In response to determining the text string includes an obsequious expression, a determination is made as to whether the obsequious expression describes the content entity. A query is forwarded in response to determining the text string includes an obsequious expression and in determining the obsequious expression describes the content entity. In response to determining the obsequious expression describes the content entity, the query includes the obsequious expression and in response to determining the obsequious expression does not describe the content entity, the query does not include the obsequious expression.

    Methods for natural language model training in natural language understanding (NLU) systems

    公开(公告)号:US12046230B2

    公开(公告)日:2024-07-23

    申请号:US18113984

    申请日:2023-02-24

    Abstract: Systems and methods for determining to perform an action of a query using a trained natural language model of a natural language understanding (NLU) system are disclosed herein. A text string corresponding to a prescribed action includes at least a content entity is received. A determination is made as to whether the text string corresponds to an audio input of a first group. In response to determining the text string corresponds to an audio input of a first group, a determination is made as to whether the text string includes an obsequious expression. In response to determining the text string corresponds to an audio input of a first group and in response to determining the text string includes an obsequious expression, a determination is made to perform the prescribed action. In response to determining the text string corresponds to an audio input of a first group and in response to determining the text string does not include the obsequious expression, a determination is made to not perform the prescribed action.

    METHODS FOR NATURAL LANGUAGE MODEL TRAINING IN NATURAL LANGUAGE UNDERSTANDING (NLU) SYSTEMS

    公开(公告)号:US20230290338A1

    公开(公告)日:2023-09-14

    申请号:US18113984

    申请日:2023-02-24

    Abstract: Systems and methods for determining to perform an action of a query using a trained natural language model of a natural language understanding (NLU) system are disclosed herein. A text string corresponding to a prescribed action includes at least a content entity is received. A determination is made as to whether the text string corresponds to an audio input of a first group. In response to determining the text string corresponds to an audio input of a first group, a determination is made as to whether the text string includes an obsequious expression. In response to determining the text string corresponds to an audio input of a first group and in response to determining the text string includes an obsequious expression, a determination is made to perform the prescribed action. In response to determining the text string corresponds to an audio input of a first group and in response to determining the text string does not include the obsequious expression, a determination is made to not perform the prescribed action.

    Methods for natural language model training in natural language understanding (NLU) systems

    公开(公告)号:US11626103B2

    公开(公告)日:2023-04-11

    申请号:US16805342

    申请日:2020-02-28

    Abstract: Systems and methods for determining to perform an action of a query using a trained natural language model of a natural language understanding (NLU) system are disclosed herein. A text string corresponding to a prescribed action includes at least a content entity is received. A determination is made as to whether the text string corresponds to an audio input of a first group. In response to determining the text string corresponds to an audio input of a first group, a determination is made as to whether the text string includes an obsequious expression. In response to determining the text string corresponds to an audio input of a first group and in response to determining the text string includes an obsequious expression, a determination is made to perform the prescribed action. In response to determining the text string corresponds to an audio input of a first group and in response to determining the text string does not include the obsequious expression, a determination is made to not perform the prescribed action.

    METHODS FOR NATURAL LANGUAGE MODEL TRAINING IN NATURAL LANGUAGE UNDERSTANDING (NLU) SYSTEMS

    公开(公告)号:US20210272553A1

    公开(公告)日:2021-09-02

    申请号:US16805335

    申请日:2020-02-28

    Abstract: Systems and methods for generating a query using a trained natural language model of a natural language understanding (NLU) system are disclosed herein. A text string including at least a content entity is received. A determination is made as to whether the text string includes an obsequious expression. In response to determining the text string includes an obsequious expression, a determination is made as to whether the obsequious expression describes the content entity. In response to determining whether the obsequious expression describes the content entity, the query is generated. In response to determining the obsequious expression describes the content entity, the content entity and the obsequious expression are included in the query and in response to determining the obsequious expression does not describe the content entity, the content entity is included in the query and the obsequious expression is excluded from the query.

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