首页> 外文会议>Information Science and Engineering (ICISE), 2009 >Tone Recognition of Continuous Mandarin Speech Based on Binary-Class SVMs
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Tone Recognition of Continuous Mandarin Speech Based on Binary-Class SVMs

机译:基于二叉级支持向量机的连续普通话语音识别

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摘要

Tone is an essential component for word formation in all tone languages. It plays a very important role in the transmission of information in speech communication. In this paper, we look at using support vector machines (SVMs) for automatic tone recognition in continuously spoken Mandarin. Wavelet transform and Teager Energy Operation (TEO) are used to detect the voiced segments. Considerable improvement has been achieved by adopting binary-SVMs scheme in a speaker-independent Mandarin tone recognition system.
机译:语调是所有语调语言中构词的重要组成部分。它在语音通信中的信息传输中起着非常重要的作用。在本文中,我们着眼于使用支持向量机(SVM)在连续说普通话中进行自动语音识别。小波变换和Teager能量运算(TEO)用于检测浊音段。通过在与说话者无关的普通话音调识别系统中采用二进制支持向量机方案,已经取得了相当大的进步。

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