利用FM和MFCC特征改进越南语声调分类

P. Le, E. Ambikairajah, E. Choi
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引用次数: 12

摘要

本文主要研究越南语语音的声调分类。传统上,音调是根据基频F0来分类或识别的。然而,我们的实验结果表明,在越南语语音中,除了基频之外,Mel频率倒频谱系数和频率调制也携带了大量的音调信息。因此,本文提出的方法综合考虑了这两类特征,提高了分类精度。实验结果表明,与仅基于F0的传统分类系统相比,该分类系统的准确率提高了7.5%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Improvement of Vietnamese Tone Classification using FM and MFCC Features
This paper focuses on tone classification for the Vietnamese speech. Traditionally, tone was classified or recognized by the fundamental frequency F0. However, our experimental results indicate that along with the fundamental frequency, Mel Frequency Cepstrum Coefficients and frequency modulation also carry a significant amount of tone information in the Vietnamese speech. Therefore, the proposed method takes into account these two types of features to improve the classification accuracy. The experimental results show that the proposed classification system provides an improvement of 7.5% in accuracy, compared to the conventional system based on F0 alone.
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