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    DELTA MODELS FOR PROVIDING PRIVATIZED SPEECH-TO-TEXT DURING VIRTUAL MEETINGS
    2.
    发明公开
    DELTA MODELS FOR PROVIDING PRIVATIZED SPEECH-TO-TEXT DURING VIRTUAL MEETINGS 审中-公开

    公开(公告)号：US20230352026A1

    公开(公告)日：2023-11-02

    申请号：US17732876

    申请日：2022-04-29

    申请人： Zoom Video Communications, Inc.

    发明人： Shane Paul Springer ,  Alexander Waibel

    IPC分类号： G10L15/26 ,  G10L15/30 ,  G10L15/183 ,  G10L15/06

    CPC分类号： G10L15/26 ,  G10L15/30 ,  G10L15/183 ,  G10L15/063 ,  G10L2015/0633

    摘要： Provided herein are systems and methods for delta models for providing privatized speech-to-text during virtual meetings. In one embodiment, a system may include a non-transitory computer-readable medium; a communications interface; and a processor. The processor may be configured to execute processor-executable instructions to: join a virtual meeting. Each participant in the virtual meeting may exchange audio streams with other participants in the virtual meeting. The instructions may include receiving, from a video conference provider, a local model for speech recognition. The local model may be a copy of a centralized model. The instructions may include performing speech recognition using the local model on the audio streams. Performing speech recognition may include identifying audio feature data within the one or more audio streams, identifying, based on a vocabulary database, user-specific vocabulary within the audio feature data, and generating, based on the user-specific vocabulary, a private transcription of the audio streams.

    Cross-Language Speech Recognition and Translation
    7.
    发明申请
    Cross-Language Speech Recognition and Translation 审中-公开
    跨语言语音识别与翻译

    公开(公告)号：US20160336008A1

    公开(公告)日：2016-11-17

    申请号：US14714046

    申请日：2015-05-15

    申请人： Microsoft Technology Licensing, LLC

    发明人： Arul A. Menezes ,  Hany M. Hassan Awadalla

    IPC分类号： G10L15/187 ,  G10L15/06 ,  G06F17/28 ,  G10L15/19 ,  G06F17/27 ,  G10L13/08

    CPC分类号： G10L15/187 ,  G06F17/278 ,  G06F17/2818 ,  G10L15/06 ,  G10L15/19 ,  G10L2015/0633

    摘要： Technologies are described herein for cross-language speech recognition and translation. An example method of speech recognition and translation includes receiving an input utterance in a first language, the input utterance having at least one name of a named entity included therein and being pronounced in a second language, utilizing a customized language model to process at least a portion of the input utterance, and identifying the at least one name of the named entity from the input utterance utilizing a phonetic representation of the at least one name of the named entity. The phonetic representation has a pronunciation of the at least one name in the second language.

    摘要翻译： 这里描述了用于跨语言语音识别和翻译的技术。 语音识别和翻译的示例性方法包括以第一语言接收输入话语，输入话语具有包括在其中的命名实体的至少一个名称并以第二语言发音，利用定制语言模型来处理至少一个 输入话语的一部分，以及利用所述命名实体的至少一个名称的语音表示，从所述输入话语中识别所述命名实体的所述至少一个名称。 语音表示具有第二语言中至少一个名称的发音。

    Machine learning dialect identification
    8.
    发明授权
    Machine learning dialect identification 有权
    机器学习方言识别

    公开(公告)号：US09477652B2

    公开(公告)日：2016-10-25

    申请号：US14621921

    申请日：2015-02-13

    申请人： Facebook, Inc.

    发明人： Fei Huang

    IPC分类号： G06F17/20 ,  G06F17/27 ,  G06F17/21 ,  G06F17/28 ,  G10L15/00 ,  G10L15/26

    CPC分类号： G10L15/063 ,  G06F17/274 ,  G06F17/275 ,  G06F17/279 ,  G06F17/28 ,  G10L15/005 ,  G10L15/26 ,  G10L2015/0633 ,  G10L2015/0636

    摘要： Technology is disclosed for creating and tuning classifiers for language dialects and for generating dialect-specific language modules. A computing device can receive an initial training data set as a current training data set. The selection process for the initial training data set can be achieved by receiving one or more initial content items, establishing dialect parameters of each of the initial content items, and sorting each of the initial content items into one or more dialect groups based on the established dialect parameters. The computing device can generate, based on the initial training data set, a dialect classifier configured to detect language dialects of content items to be classified. The computing device can augment the current training data set with additional training data by applying the dialect classifier to candidate content items. The computing device can then update the dialect classifier based on the augmented current training data set.

    摘要翻译： 公开了用于创建和调整用于语言方言的分类器和用于生成方言特定语言模块的技术。 计算设备可以接收初始训练数据集作为当前训练数据集。 初始训练数据集的选择过程可以通过接收一个或多个初始内容项目，建立每个初始内容项目的方言参数，并且基于所建立的内容项目将每个初始内容项目分类成一个或多个方言组来实现 方言参数。 计算设备可以基于初始训练数据集生成被配置为检测要分类的内容项的语言方言的方言分类器。 计算设备可以通过将方言分类器应用于候选内容项来增加具有附加训练数据的当前训练数据集。 然后，计算设备可以基于增强的当前训练数据集来更新方言分类器。