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    METHOD AND APPARATUS FOR SPEAKER RECOGNITION
    1.
    发明申请
    METHOD AND APPARATUS FOR SPEAKER RECOGNITION 审中-公开
    用于语音识别的方法和装置

    公开(公告)号：US20080010065A1

    公开(公告)日：2008-01-10

    申请号：US11758650

    申请日：2007-06-05

    申请人： Harry BRATT ,  Luciana Ferrer ,  Martin Graciarena ,  Sachin Kajarekar ,  Elizabeth Shriberg ,  Mustafa Sonmez ,  Andreas Stolcke ,  Gokhan Tur ,  Anand Venkataraman

    发明人： Harry BRATT ,  Luciana Ferrer ,  Martin Graciarena ,  Sachin Kajarekar ,  Elizabeth Shriberg ,  Mustafa Sonmez ,  Andreas Stolcke ,  Gokhan Tur ,  Anand Venkataraman

    IPC分类号： G10L17/00

    CPC分类号： G06K9/6222 ,  G10L17/10

    摘要： A method and apparatus for speaker recognition is provided. One embodiment of a method for determining whether a given speech signal is produced by an alleged speaker, where a plurality of statistical models (including at least one support vector machine) have been produced for the alleged speaker based on a previous speech signal received from the alleged speaker, includes receiving the given speech signal, the speech signal representing an utterance made by a speaker claiming to be the alleged speaker, scoring the given speech signal using at least two modeling systems, where at least one of the modeling systems is a support vector machine, combining scores produced by the modeling systems, with equal weights, to produce a final score, and determining, in accordance with the final score, whether the speaker is likely the alleged speaker.

    摘要翻译： 提供了一种用于说话者识别的方法和装置。 一种用于确定给定语音信号是否由所指示的说话者产生的方法的一个实施例，其中已经根据从所述语音信号接收到的先前语音信号为所述说话者产生了多个统计模型（包括至少一个支持向量机） 所述扬声器包括接收给定的语音信号，所述语音信号表示由声称是所述说话者的扬声器发出的发声，使用至少两个建模系统对所述给定语音信号进行评分，其中所述建模系统中的至少一个是支持 向量机，组合由建模系统产生的得分，具有相等的权重，以产生最终得分，并且根据最终得分确定说话人是否可能是被指称的说话者。

    Method and apparatus for active noise cancellation
    6.
    发明申请
    Method and apparatus for active noise cancellation 有权
    主动噪声消除的方法和装置

    公开(公告)号：US20080082326A1

    公开(公告)日：2008-04-03

    申请号：US11541282

    申请日：2006-09-28

    申请人： Anand Venkataraman ,  Venkata Ramana Rao Gadde ,  Martin Graciarena

    发明人： Anand Venkataraman ,  Venkata Ramana Rao Gadde ,  Martin Graciarena

    IPC分类号： G10L21/02

    CPC分类号： G10L15/20 ,  G10L21/02 ,  G10L2015/088

    摘要： In one embodiment, the present invention is a method and apparatus for active noise cancellation. In one embodiment, a method for recognizing user speech in an audio signal received by a media system (where the audio signal includes user speech and ambient audio output produced by the media system and/or other devices) includes canceling portions of the audio signal associated with the ambient audio output and applying speech recognition processing to an uncancelled remainder of the audio signal.

    摘要翻译： 在一个实施例中，本发明是用于主动噪声消除的方法和装置。 在一个实施例中，用于识别由媒体系统（其中音频信号包括由媒体系统和/或其他设备产生的用户语音和环境音频输出）接收的音频信号中的用户语音的方法包括消除相关联的音频信号的部分 与环境音频输出并且将语音识别处理应用于音频信号的未被取消的剩余部分。

    Method and apparatus for active noise cancellation
    7.
    发明授权
    Method and apparatus for active noise cancellation 有权
    主动噪声消除的方法和装置

    公开(公告)号：US07769593B2

    公开(公告)日：2010-08-03

    申请号：US11541282

    申请日：2006-09-28

    申请人： Anand Venkataraman ,  Venkata Ramana Rao Gadde ,  Martin Graciarena

    发明人： Anand Venkataraman ,  Venkata Ramana Rao Gadde ,  Martin Graciarena

    IPC分类号： G10L15/00

    CPC分类号： G10L15/20 ,  G10L21/02 ,  G10L2015/088

    摘要： In one embodiment, the present invention is a method and apparatus for active noise cancellation. In one embodiment, a method for recognizing user speech in an audio signal received by a media system (where the audio signal includes user speech and ambient audio output produced by the media system and/or other devices) includes canceling portions of the audio signal associated with the ambient audio output and applying speech recognition processing to an uncancelled remainder of the audio signal.

    摘要翻译： 在一个实施例中，本发明是用于主动噪声消除的方法和装置。 在一个实施例中，用于识别由媒体系统（其中音频信号包括由媒体系统和/或其他设备产生的用户语音和环境音频输出）接收的音频信号中的用户语音的方法包括消除相关联的音频信号的部分 与环境音频输出并且将语音识别处理应用于音频信号的未被取消的剩余部分。

    Method and apparatus for recognizing speech in a noisy environment
    8.
    发明授权
    Method and apparatus for recognizing speech in a noisy environment 有权
    在嘈杂环境中识别语音的方法和装置

    公开(公告)号：US07571095B2

    公开(公告)日：2009-08-04

    申请号：US11216669

    申请日：2005-08-31

    申请人： Martin Graciarena ,  Horacio Franco ,  Venkata Ramana Rao Gadde

    发明人： Martin Graciarena ,  Horacio Franco ,  Venkata Ramana Rao Gadde

    IPC分类号： G10L15/20

    CPC分类号： G10L15/20

    摘要： An apparatus and a concomitant method for recognizing speech in a noisy environment are provided. The present method includes applying a first interpolation weight to a clean speech model to produce a weighted clean speech model, applying a second interpolation weight to a noise model to produce a weighted noise model, and deriving a noisy speech model directly from the weighted clean speech model and the weighted noise model. At least one of the first interpolation weight and the second interpolation weight is computed in a maximum likelihood framework.

    摘要翻译： 提供了一种用于在嘈杂环境中识别语音的装置和伴随方法。 本方法包括对干净的语音模型应用第一内插权重以产生加权的干净语音模型，将第二内插权重应用于噪声模型以产生加权噪声模型，以及从加权干净语音直接导出噪声语音模型 模型和加权噪声模型。 在最大似然框架中计算第一插值权重和第二插值权重中的至少一个。

    Method and apparatus for recognizing speech in a noisy environment
    9.
    发明申请
    Method and apparatus for recognizing speech in a noisy environment 有权

    公开(公告)号：US20060195317A1

    公开(公告)日：2006-08-31

    申请号：US11216669

    申请日：2005-08-31

    申请人： Martin Graciarena ,  Horacio Franco ,  Venkata Gadde

    发明人： Martin Graciarena ,  Horacio Franco ,  Venkata Gadde

    IPC分类号： G10L15/20

    CPC分类号： G10L15/20

    摘要： An apparatus and a concomitant method for recognizing speech in a noisy environment are provided. The present method includes applying a first interpolation weight to a clean speech model to produce a weighted clean speech model, applying a second interpolation weight to a noise model to produce a weighted noise model, and deriving a noisy speech model directly from the weighted clean speech model and the weighted noise model. At least one of the first interpolation weight and the second interpolation weight is computed in a maximum likelihood framework.