一种新的两步支持向量机分类器,用于语音的浊音/静音分类

Fengyan Qi, C. Bao, Yan Liu
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引用次数: 33

摘要

本文提出了一种基于支持向量机(SVM)的语音清/不清/静音分类新方法。该分类器能够正确地将语音帧分为浊音帧、浊音帧和静音帧。实验结果表明,该方法优于其他传统方法。对实验中不同核函数下支持向量机的性能进行了分析和讨论。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A novel two-step SVM classifier for voiced/unvoiced/silence classification of speech
In this paper, a novel method for voiced/unvoiced/silence of speech classification using the support vector machine (SVM) is proposed. This classifier can correctly classify speech frames into voiced frame, unvoiced frame and silence frame. The comparison of experimental results show that the proposed method outperforms other traditional methods. The performance of SVM for different kernel functions in the experiment was analyzed and discussed as well.
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