Applying wavelet analysis to speech segmentation and classification
Applying wavelet analysis to speech segmentation and classification
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将小波分析应用于语音分割和分类
DOI：
10.1117/12.170075
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发表时间：
1994
期刊：
影响因子：
--
通讯作者：
P. Dermody
中科院分区：
文献类型：
--
作者：
B. T. Tan;R. Lang;H. Schroder;A. Spray;P. Dermody
提出了一种基于小波变换的助听器设计方案。采用快速小波变换将语音分解成不同的频率分量。本文介绍了在语音处理中使用小波变换的困难，并展示了如何仔细选择小波系数可以使语音的四大类-浊音，起爆音，摩擦音和沉默-被识别。通过对这四种类型的了解，本文展示了如何轻松有效地对语音进行分词。
We propose the design of a hearing aid based on the wavelet transform. The fast wavelet transform is used to decompose speech into different frequency components. This paper presents the difficulties in the use of wavelet transforms for speech processing and shows how the careful selection of wavelet coefficients can enable the four major categories of speech - voiced speech, plosives, fricatives, and silence - to be identified. With knowledge of these four categories, it is shown how speech can be easily and effectively segmented.