A Study on Speech Endpoint Detection and Applications
碩士 === 大葉大學 === 電機工程學系 === 103 === In this research we discuss the effect between endpoint detection and speech recognition. First we refer to HTK’s endpoint detection. We use MATLAB to design a program to change the threshold constants for five kinds of SNR wave files. Each SNR wave files can obt...
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ndltd-TW-103DYU004420312016-07-16T04:11:57Z http://ndltd.ncl.edu.tw/handle/38763613104682958616 A Study on Speech Endpoint Detection and Applications 語音端點偵測與應用 Li Wen-Zuo 李文祚 碩士 大葉大學 電機工程學系 103 In this research we discuss the effect between endpoint detection and speech recognition. First we refer to HTK’s endpoint detection. We use MATLAB to design a program to change the threshold constants for five kinds of SNR wave files. Each SNR wave files can obtain a best threshold constant. This optimization of threshold constant have 1.2%~3.9% endpoint detection error improvement than HTK’s endpoint detection. But SNR5 and SNR0 wave files have 39.5% and 37.0% endpoint detection error improvement. Then we improve the endpoint detection by adding zero crossing rate endpoint detection. We get 20.8%~46.29% endpoint detection error improvement for all kinds of SNR wave files. Especially on SNR20 wave files have 50.86% endpoint detection error improvement. Finally, we put both HTK’s endpoint detection and our endpoint detection results into a speech recognition system. On the least noise wave files. The recognition rate of HTK’s endpoint detection and our endpoint detection are 98.64% and 99.01%. Each SNR wave files have 0.37%~6.57% recognition rate improvement. Even on SNR10 and SNR5 wave files have 31.94% and 21.49% improvement of recognition rate. Lee Lee-Min 李立民 2015 學位論文 ; thesis 61 zh-TW |
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碩士 === 大葉大學 === 電機工程學系 === 103 === In this research we discuss the effect between endpoint detection and speech recognition. First we refer to HTK’s endpoint detection. We use MATLAB to design a program to change the threshold constants for five kinds of SNR wave files. Each SNR wave files can obtain a best threshold constant. This optimization of threshold constant have 1.2%~3.9% endpoint detection error improvement than HTK’s endpoint detection. But SNR5 and SNR0 wave files have 39.5% and 37.0% endpoint detection error improvement. Then we improve the endpoint detection by adding zero crossing rate endpoint detection. We get 20.8%~46.29% endpoint detection error improvement for all kinds of SNR wave files. Especially on SNR20 wave files have 50.86% endpoint detection error improvement. Finally, we put both HTK’s endpoint detection and our endpoint detection results into a speech recognition system. On the least noise wave files. The recognition rate of HTK’s endpoint detection and our endpoint detection are 98.64% and 99.01%. Each SNR wave files have 0.37%~6.57% recognition rate improvement. Even on SNR10 and SNR5 wave files have 31.94% and 21.49% improvement of recognition rate.
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Lee Lee-Min |
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Lee Lee-Min Li Wen-Zuo 李文祚 |
author |
Li Wen-Zuo 李文祚 |
spellingShingle |
Li Wen-Zuo 李文祚 A Study on Speech Endpoint Detection and Applications |
author_sort |
Li Wen-Zuo |
title |
A Study on Speech Endpoint Detection and Applications |
title_short |
A Study on Speech Endpoint Detection and Applications |
title_full |
A Study on Speech Endpoint Detection and Applications |
title_fullStr |
A Study on Speech Endpoint Detection and Applications |
title_full_unstemmed |
A Study on Speech Endpoint Detection and Applications |
title_sort |
study on speech endpoint detection and applications |
publishDate |
2015 |
url |
http://ndltd.ncl.edu.tw/handle/38763613104682958616 |
work_keys_str_mv |
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