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Minimum of Information Divergence Criterion for Signals with Tuning to Speaker Voice in Automatic Speech Recognition

机译:用于在自动语音识别中调谐到扬声器语音的信号的信息分歧标准

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摘要

It is considered a problem of automatic speech recognition at basic, phonetic level of speech signal processing. It is researched a problem of noise-immunity increase. For its solution it is proposed a criterion of minimum information divergence of the signals with tuning to a speaker voice and automatic scaling of speech template to thin structure of observed (current) speech frame. An example of its practical realization is considered, efficiency characteristics are researched. Applying the author’s software we carry out an experiment and obtain qualitative estimations of threshold signals gain in case of application of proposed criterion. It is shown than this gain can be 10 dB and greater under certain conditions. Obtained results and drawn conclusions are intended it to their application for development and modernization of existent systems and techniques of automatic processing and recognition of speech intended it to operation in conditions of intensive noise effect.
机译:它被认为是语音信号处理的基本,语音级别的自动语音识别问题。研究了抗噪性的问题。对于其解决方案,提出了具有调谐到扬声器语音的信号的最小信息发散的标准,以及语音模板的自动扩展到观察到的(电流)语音帧的薄结构。考虑了其实际实现的一个例子,研究了效率特征。应用作者的软件我们执行实验,并在应用提出标准的情况下获得阈值信号的定性估计。它显示在某些条件下,该增益可以是10 dB,更大。获得的结果和得出的结论是为了其应用于其现有系统的开发和现代化应用以及识别言论的识别,以便在密集噪声效应条件下进行操作。

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