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RECURSIVE SPEAKER ADAPTATION AUTOMATION SPEECH RECOGNITION SYSTEM AND METHOD USING EIGENVOICE SPEAKER ADAPTATION

机译:使用本征语音自适应的递归扬声​​器自适应自动语音识别系统和方法

摘要

The present invention recursively speaker adaptive speech recognition system and to a method, recognizes the input talker speech 1st, and compare with the negative results of the primary recognition four (Unsupervised Adaptation) method using a specific sound speaker adaptation own voice (EigenVoice) may be performed after the speaker adaptation, using the speaker-adapted acoustic models to further improve the recognition rate by recognizing the speaker's voice to the second enemy.; The invention of using the extracted the feature vectors used in speech recognition from an input speech signal, the voice characteristic extraction unit, and a speaker independent acoustic model has already been trained and the extracted feature vectors recognition vocabulary of the speech signals 1 and primary recognizer, the first recognition unit recognizes the result of the label information with the voice characteristic extraction unit feature vector in reference to observed data to the speaker adaptation section for performing speaker adaptation, and speaker dependent acoustic models provided by the speaker adaptation section used to be constituted by the second recognition and outputting a recognition result of the speech signal.
机译:本发明递归的说话者自适应语音识别系统和方法,识别输入的说话者语音第一,并且与使用特定声音的说话者自适应自己的声音(EigenVoice)的主要识别四(无监督自适应)方法的否定结果进行比较。在说话人适应之后执行,使用说话人自适应的声学模型通过识别说话人对第二个敌人的声音来进一步提高识别率。已经训练了使用从输入语音信号,语音特性提取单元和与说话者无关的声学模型中提取用于语音识别的特征矢量的发明,并且提取了语音信号1和主识别器的提取的特征矢量识别词汇,第一识别单元参考语音数据提取单元特征向量,识别标签信息的结果,该特征矢量参考观察到的数据,以进行说话者自适应的说话者自适应部分,以及由说话者自适应部分提供的依赖于说话者的声学模型来构成通过第二识别并输出语音信号的识别结果。

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