LANGUAGE MODEL TRANSLATION AND TRAINING METHOD AND APPARATUS

    公开(公告)号:US20190163747A1

    公开(公告)日:2019-05-30

    申请号:US15947915

    申请日:2018-04-09

    Abstract: A language model training method and an apparatus using the language model training method are disclosed. The language model training method includes assigning a context vector to a target translation vector, obtaining feature vectors based on the target translation vector and the context vector, generating a representative vector representing the target translation vector using an attention mechanism for the feature vectors, and training a language model based on the target translation vector, the context vector, and the representative vector.

    DECODING METHOD AND APPARATUS IN ARTIFICIAL NEURAL NETWORK FOR SPEECH RECOGNITION

    公开(公告)号:US20230306961A1

    公开(公告)日:2023-09-28

    申请号:US18321876

    申请日:2023-05-23

    CPC classification number: G10L15/16

    Abstract: A decoding method and apparatus in an artificial neural network for speech recognition. The decoding method in the artificial neural network for speech recognition includes performing a first decoding task of decoding a feature including speech information and at least one token recognized up to current time, using a shared decoding layer included in the artificial neural network, performing a second decoding task of decoding the at least one token, using the shared decoding layer, and determining an output token to be recognized subsequent to the at least one token based on a result of the first decoding task and a result of the second decoding task.

    SPEECH SIGNAL PROCESSING METHOD AND APPARATUS

    公开(公告)号:US20220020362A1

    公开(公告)日:2022-01-20

    申请号:US17106599

    申请日:2020-11-30

    Inventor: Tae Gyoon KANG

    Abstract: A speech signal processing method and apparatus is disclosed. The speech signal processing method includes receiving an input token that is based on a speech signal, calculating first probability values respectively corresponding to candidate output tokens based on the input token, adjusting at least one of the first probability values based on a priority of each of the first probability values, and processing the speech signal based on an adjusted probability value obtained by the adjusting.

    DECODING METHOD AND APPARATUS IN ARTIFICIAL NEURAL NETWORK FOR SPEECH RECOGNITION

    公开(公告)号:US20210035562A1

    公开(公告)日:2021-02-04

    申请号:US16844401

    申请日:2020-04-09

    Abstract: A decoding method and apparatus in an artificial neural network for speech recognition. The decoding method in the artificial neural network for speech recognition includes performing a first decoding task of decoding a feature including speech information and at least one token recognized up to current time, using a shared decoding layer included in the artificial neural network, performing a second decoding task of decoding the at least one token, using the shared decoding layer, and determining an output token to be recognized subsequent to the at least one token based on a result of the first decoding task and a result of the second decoding task.

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