In-Vehicle Speech Interaction Method and Device

    公开(公告)号:US20230048330A1

    公开(公告)日:2023-02-16

    申请号:US17976339

    申请日:2022-10-28

    Abstract: An in-vehicle speech interaction method and a device are provided. The method includes: obtaining user speech information; determining a user instruction based on the user speech information; determining, based on the user instruction, whether response content to the user instruction is privacy-related; and determining, based on whether the response content is privacy-related, whether to output the response content in a privacy protection mode, to protect privacy from being leaked.

    Filtering Model Training Method and Speech Recognition Method

    公开(公告)号:US20200258499A1

    公开(公告)日:2020-08-13

    申请号:US16861856

    申请日:2020-04-29

    Inventor: Weiran Nie Hai Yu

    Abstract: A filtering model training method includes obtaining N original syllables, obtaining N recognized syllables, and obtaining N syllable distances based on the N original syllables and the N recognized syllables, where the N syllable distances are in a one-to-one correspondence with N syllable pairs, the N original syllables and the N recognized syllables form the N syllable pairs, each syllable pair includes an original syllable and a recognized syllable that correspond to each other, and each syllable distance is used to indicate a similarity between an original syllable and a recognized syllable that are included in a corresponding syllable pair.

    Filtering model training method and speech recognition method

    公开(公告)号:US11211052B2

    公开(公告)日:2021-12-28

    申请号:US16861856

    申请日:2020-04-29

    Inventor: Weiran Nie Hai Yu

    Abstract: A filtering model training method includes obtaining N original syllables, obtaining N recognized syllables, and obtaining N syllable distances based on the N original syllables and the N recognized syllables, where the N syllable distances are in a one-to-one correspondence with N syllable pairs, the N original syllables and the N recognized syllables form the N syllable pairs, each syllable pair includes an original syllable and a recognized syllable that correspond to each other, and each syllable distance is used to indicate a similarity between an original syllable and a recognized syllable that are included in a corresponding syllable pair.

    INTERFACE CONTROL METHOD AND APPARATUS, AND SYSTEM

    公开(公告)号:US20240126503A1

    公开(公告)日:2024-04-18

    申请号:US18397864

    申请日:2023-12-27

    CPC classification number: G06F3/167

    Abstract: This application provides an interface control method. The method includes: obtaining a speech instruction of a user and a sound source location of the user; obtaining line-of-sight information of the user; determining a target window on an interface based on the sound source location and the line-of-sight information; and controlling the target window based on the speech instruction. According to the interface control method in this application, collaborative decision-making is performed with reference to multimode information such as sound source information, line-of-sight tracking information, speech semantic information, and priorities thereof, so that page content in a plurality of windows on the interface is quickly and accurately controlled, to improve user experience.

    SPEECH RECOGNITION METHOD, APPARATUS, AND DEVICE, AND COMPUTER-READABLE STORAGE MEDIUM

    公开(公告)号:US20220093087A1

    公开(公告)日:2022-03-24

    申请号:US17539005

    申请日:2021-11-30

    Abstract: A speech recognition method, apparatus, and device, and a computer-readable storage medium provided pertain to the field of artificial intelligence technologies. The method includes: obtaining or generating a dynamic target language model based on reply information of a first intent, where the dynamic target language model includes a front-end part and a core part; obtaining a speech signal, parsing the speech signal to generate a key word; and invoking the dynamic target language model to determine a second intent and a service content. The front-end part of the dynamic target language model parses out the second intent based on the key word, and the core part of the dynamic target language model parses out the service content based on the key word. The speech recognition method prevents a provided service content from deviating from a user requirement and achieves a good recognition effect.

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