METHOD AND APPARATUS FOR SPEECH RECOGNITION

    公开(公告)号:US20230076073A1

    公开(公告)日:2023-03-09

    申请号:US17986000

    申请日:2022-11-14

    Inventor: Min-Joong LEE

    Abstract: A speech recognition method includes adding a preset special sequence to a front end of an input sequence that corresponds to an input utterance of a speaker, recognizing the preset special sequence and the input sequence, and recognizing the input sequence based on the preset special sequence and a speech recognition result obtained by recognizing the preset special sequence and the input sequence.

    METHOD AND APPARATUS FOR SPEECH RECOGNITION
    3.
    发明申请

    公开(公告)号:US20200320983A1

    公开(公告)日:2020-10-08

    申请号:US16787701

    申请日:2020-02-11

    Inventor: Min-Joong LEE

    Abstract: A speech recognition method includes adding a preset special sequence to a front end of an input sequence that corresponds to an input utterance of a speaker, recognizing the preset special sequence and the input sequence, and recognizing the input sequence based on the preset special sequence and a speech recognition result obtained by recognizing the preset special sequence and the input sequence.

    METHOD AND APPARATUS WITH SPEECH RECOGNITION

    公开(公告)号:US20200090642A1

    公开(公告)日:2020-03-19

    申请号:US16385047

    申请日:2019-04-16

    Inventor: Min-Joong LEE

    Abstract: A processor-implemented speech recognition method includes: extracting a speech feature from an input speech to be recognized; estimating a first sequence of first subwords corresponding to at least one portion of the input speech based on the extracted speech feature; converting the first sequence to a second sequence of at least one second subword by combining at least two of the first subwords; and recognizing the input speech by recognizing a remaining portion of the input speech based on the second sequence.

    METHOD AND APPARATUS WITH UTTERANCE TIME ESTIMATION

    公开(公告)号:US20210358493A1

    公开(公告)日:2021-11-18

    申请号:US17064879

    申请日:2020-10-07

    Inventor: Min-Joong LEE

    Abstract: A processor-implemented utterance time estimation method includes: determining a plurality of attention weight matrices using an attention-based sequence-to-sequence model; selecting an attention weight matrix from the plurality of attention weight matrices; and estimating an utterance time corresponding to an output sequence based on the selected attention weight matrix.

    METHOD AND APPARATUS WITH SPEECH RECOGNITION

    公开(公告)号:US20200152180A1

    公开(公告)日:2020-05-14

    申请号:US16388930

    申请日:2019-04-19

    Inventor: Min-Joong LEE

    Abstract: A processor-implemented decoding method in a first neural network is provided. The method predicts probabilities of candidates of an output token based on at least one previously input token, determines the output token among the candidates based on the predicted probabilities; and determines a next input token by selecting one of the output token and a pre-defined special token based on a determined probability of the output token.

    METHOD AND APPARATUS FOR IMPROVING QUALITY OF ATTENTION-BASED SEQUENCE-TO-SEQUENCE MODEL

    公开(公告)号:US20210366501A1

    公开(公告)日:2021-11-25

    申请号:US17109490

    申请日:2020-12-02

    Inventor: Min-Joong LEE

    Abstract: A method and apparatus for improving the quality of an attention-based sequence-to-sequence model. The method includes determining an output sequence corresponding to an input sequence based on an attention-based sequence-to-sequence model, selecting at least one target attention head from among a plurality of attention heads, detecting at least one error output token among output tokens constituting the output sequence based on the target attention head, and correcting the output sequence based on the error output token.

    LANGUAGE PROCESSING METHOD AND APPARATUS
    9.
    发明申请

    公开(公告)号:US20190172466A1

    公开(公告)日:2019-06-06

    申请号:US16108717

    申请日:2018-08-22

    Abstract: A language processing method and apparatus is disclosed. A language processing apparatus using a neural network may obtain context information from a source text using a neural network-based encoder, generate a prefix token from the context information using a neural network-based main decoder, generate a token sequence including at least two successive tokens sequentially following the prefix token using a skip model in response to the prefix token satisfying a preset condition, and indicate a target text in which the prefix token and the token sequence are combined as an inference result with respect to the source text.

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