SYSTEMS AND METHODS FOR DETECTING A MIMICKED VOICE INPUT SIGNAL

    公开(公告)号:US20220148600A1

    公开(公告)日:2022-05-12

    申请号:US17095338

    申请日:2020-11-11

    Abstract: Methods and systems are disclosed herein for training a network to detect mimicked voice input, so that it can be determined whether a voice input signal is a mimicked voice signal. First voice data is received. The first voice data comprises at least a voice signal of a first individual and another voice signal. The voice signal of the first individual and at least one other voice signal is combined to create a composite voice signal. Second voice data is received. The second voice data comprises at least a voice signal of the first individual. The network is trained using at least the composite voice signal and the second voice data to determine whether a voice input signal is a mimicked voice input signal.

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

    公开(公告)号:US11574127B2

    公开(公告)日:2023-02-07

    申请号:US16805358

    申请日:2020-02-28

    Abstract: Systems and methods for training a classifier binary model of a natural language understanding (NLU) system are disclosed herein. A determination is made as to whether a text string, with a content entity, 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. The model is trained based on a determination of at least one of: an absence of an obsequious expression in response to determining the obsequious expression describes the content entity; a presence of an obsequious expression in response to determining the obsequious expression describes the content entity; an absence of an obsequious expression in response to determining the obsequious expression does not describe the content entity, and a presence of an obsequious expression in response to determining the obsequious expression does not describe the content entity.

    SYSTEM AND METHOD FOR GENERATING PERSONALIZED VIDEO TRAILERS

    公开(公告)号:US20220157348A1

    公开(公告)日:2022-05-19

    申请号:US17591358

    申请日:2022-02-02

    Abstract: Systems and methods for generating individualized content trailers. Content such as a video is divided into segments each representing a set of common features. With reference to a set of stored user preferences, certain segments are selected as aligning with the user's interests. Each selected segment may then be assigned a label corresponding to the plot portion or element to which it belongs. A coherent trailer may then be assembled from the selected segments, ordered according to their plot elements. This allows a user to see not only segments containing subject matter that aligns with their interests, but also a set of such segments arranged to give the user an idea of the plot, and a sense of drama, increasing the likelihood of engagement with the content.

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

    公开(公告)号:US20210272554A1

    公开(公告)日:2021-09-02

    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:US20210271819A1

    公开(公告)日:2021-09-02

    申请号:US16805358

    申请日:2020-02-28

    Abstract: Systems and methods for training a classifier binary model of a natural language understanding (NLU) system are disclosed herein. A determination is made as to whether a text string, with a content entity, 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. The model is trained based on a determination of at least one of: an absence of an obsequious expression in response to determining the obsequious expression describes the content entity; a presence of an obsequious expression in response to determining the obsequious expression describes the content entity; an absence of an obsequious expression in response to determining the obsequious expression does not describe the content entity, and a presence of an obsequious expression in response to determining the obsequious expression does not describe the content entity.

    SYSTEMS AND METHODS FOR MANAGING VOICE QUERIES USING PRONUNCIATION INFORMATION

    公开(公告)号:US20210035587A1

    公开(公告)日:2021-02-04

    申请号:US16528550

    申请日:2019-07-31

    Abstract: The system identifies one or more entities or content items among a plurality of stored information. The system generates an audio file based on a first text string that represents the entity or content item. Based on the first text string and at least one speech criterion, the system generating, using a speech-to-text module a second text string based on the audio file. The system then compares the text strings and stores the second text string if it is not identical to the first text string. The system generates metadata that includes results from text-speech-text conversions to forecast possible misidentifications when responding to voice queries during search operations. The metadata includes alternative representations of the entity, to improve reachability in cases where the speech-to-text conversion does generate a pr

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