论文标题
基于小波变换的方案，以提取语音音调和共振峰频率
A Wavelet Transform Based Scheme to Extract Speech Pitch and Formant Frequencies
论文作者
论文摘要
音高和共振峰频率是语音处理应用中的重要特征。声带的元音输出周期称为音高或基本频率，共振频率本质上是声带的共振频率。这些特征在不同的人甚至单词之间有所不同，但它们在一定频率范围内。实际上，只有前三个实力足以容纳大多数语音处理。特征提取和分类是每个语音识别系统的主要组成部分。在本文中，提出了两种基于小波的方法，以帮助借助过滤器库的想法提取上述功能。通过比较几个语音信号上提出的特征提取方法的结果，发现小波变换与Cepstrum方法相比具有良好的精度，并且对噪声没有敏感性。此外，审查了几种基于模糊的语音处理分类技术。
Pitch and Formant frequencies are important features in speech processing applications. The period of the vocal cord's output for vowels is known as the pitch or the fundamental frequency, and formant frequencies are essentially resonance frequencies of the vocal tract. These features vary among different persons and even words, but they are within a certain frequency range. In practice, just the first three formants are enough for the most of speech processing. Feature extraction and classification are the main components of each speech recognition system. In this article, two wavelet based approaches are proposed to extract the mentioned features with help of the filter bank idea. By comparing the results of the presented feature extraction methods on several speech signals, it was found out that the wavelet transform has a good accuracy compared to the cepstrum method and it has no sensitivity to noise. In addition, several fuzzy based classification techniques for speech processing are reviewed.
