SYSTEMS AND METHODS TO SUPPORT A NEW LOCALE IN A LANGUAGE MODEL

    公开(公告)号:US20240330609A1

    公开(公告)日:2024-10-03

    申请号:US18742539

    申请日:2024-06-13

    CPC classification number: G06F40/58 H04L67/04 H04L67/52

    Abstract: Systems and methods are presented herein for generating a new language understanding model, based on a user request. A user may input a root language and a locale into an application for generating a student language model. The application may generate the student language model and may identify a teacher language model related to the student language model. The application may compare data from the identified teacher language model to the student language model. The application may determine a subset of data from the teacher language model is not contained in the student language model. If the application determines at least a subset of data from the teacher language model is not in the student language model, the application may add at least the subset of data from the teacher language model to the student language model.

    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.

    Systems and methods to support a new locale in a language model

    公开(公告)号:US12039265B2

    公开(公告)日:2024-07-16

    申请号:US17108549

    申请日:2020-12-01

    CPC classification number: G06F40/279 G06F16/2455 G06F40/263 G06N20/00

    Abstract: Systems and methods are presented herein for generating a new language understanding model, based on a user request. A user may input a root language and a locale into an application for generating a student language model. The application may generate the student language model and may identify a teacher language model related to the student language model. The application may compare data from the identified teacher language model to the student language model. The application may determine a subset of data from the teacher language model is not contained in the student language model. If the application determines at least a subset of data from the teacher language model is not in the student language model, the application may add at least the subset of data from the teacher language model to the student language model.

    Systems and methods for avoiding inadvertently triggering a voice assistant

    公开(公告)号:US12002466B2

    公开(公告)日:2024-06-04

    申请号:US17984394

    申请日:2022-11-10

    CPC classification number: G10L15/22 G10L25/18 G10L25/60 G10L2015/223

    Abstract: Systems and methods are provided herein for avoiding inadvertently trigging a voice assistant with audio played through a speaker. An audio signal is captured by sampling a microphone of the voice assistant at a sampling frequency that is higher than an expected finite sampling frequency of previously recorded audio played through the speaker to generate a voice data sample. A quality metric of the generated voice data sample is calculated by determining whether the generated voice data sample comprises artifacts resulting from previous compression or approximation by the expected finite sampling frequency. Based on the calculated quality metric, it is determined whether the captured audio signal is previously recorded audio played through the speaker. Responsive to the determination that the captured audio signal is previously recorded audio played through the speaker, the voice assistant refrains from being activated.

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