小波变换在语音信号处理中的优势

IF 0.2 Q4 ENGINEERING, GEOLOGICAL
Sayora Ibragimova
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引用次数: 1

摘要

本文介绍了小波变换的基本理论和语音信号的多尺度分析,简要介绍了小波变换与傅立叶变换在语音信号分析中的主要区别。将小波分析方法应用于语音识别系统的可能性及其主要优点。在大多数现有的语音识别和分析系统中,语音被认为是一个向量流,其元素是某种频率响应。因此,使用序列算法进行实时语音处理需要高性能的计算资源。在处理语音信号和为识别系统建立标准时如何使用该方法的示例。关键词:数字信号处理,傅里叶变换,小波分析,语音信号,小波变换
本文章由计算机程序翻译,如有差异,请以英文原文为准。
THE ADVANTAGE OFTHEWAVELET TRANSFORM IN PROCESSING OF SPEECH SIGNALS
This work deals with basic theory of wavelet transform and multi-scale analysis of speech signals, briefly reviewed the main differences between wavelet transform and Fourier transform in the analysis of speech signals. The possibilities to use the method of wavelet analysis to speech recognition systems and its main advantages. In most existing systems of recognition and analysis of speech sound considered as a stream of vectors whose elements are some frequency response. Therefore, the speech processing in real time using sequential algorithms requires computing resources with high performance. Examples of how this method can be used when processing speech signals and build standards for systems of recognition.Key words: digital signal processing, Fourier transform, wavelet analysis, speech signal, wavelet transform
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来源期刊
Archives for Technical Sciences
Archives for Technical Sciences ENGINEERING, GEOLOGICAL-
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