Research of Speaker Independent Spoken MandarinSpoken Word Recognition System
碩士 === 中原大學 === 資訊工程研究所 === 89 === In this thesis, a speaker-independent Mandarin spoken word recog-nition system for Taiwan railway station is implemented. The system is built with components that include a Pentium PC, Microsoft Windows 98 operation system, Microsoft Visual C++ 6.0 and I...
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ndltd-TW-089CYCU53920072016-07-06T04:10:06Z http://ndltd.ncl.edu.tw/handle/99112543444173635176 Research of Speaker Independent Spoken MandarinSpoken Word Recognition System 不特定語者國語語音字詞辨識系統研究 Jia-Hui Li 李佳慧 碩士 中原大學 資訊工程研究所 89 In this thesis, a speaker-independent Mandarin spoken word recog-nition system for Taiwan railway station is implemented. The system is built with components that include a Pentium PC, Microsoft Windows 98 operation system, Microsoft Visual C++ 6.0 and Intel Recognition Primi-tives Library. During the acoustic-model training stage, we employ the energy dip, zero crossing rate, and autocorrelation function to segment speech sounds. And use the MFCC (mel scale filter cepstral coefficient) to evaluate fea-ture parameters. Through the process of Binary splitting the vector quan-tization codebooks are found, the DHMM (Discrete Hidden Markov Models) is used to establish all acoustic-models, and the BaumWelch al-gorithm is chosen to adapt the optimal solution. On the recognition part, the Kohonon Network is used to calculate codeword sequence. The Beam search is used to replacement of Viterbi algorithm that gives the best re-sult of recognition in DHMM. The recognition rates of speaker-independent experiments can reach up to 85.75%. It shows that the system has achieved good performance. Chu-Kuei Tu 杜筑奎 2001 學位論文 ; thesis 63 zh-TW |
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碩士 === 中原大學 === 資訊工程研究所 === 89 === In this thesis, a speaker-independent Mandarin spoken word recog-nition system for Taiwan railway station is implemented. The system is built with components that include a Pentium PC, Microsoft Windows 98 operation system, Microsoft Visual C++ 6.0 and Intel Recognition Primi-tives Library.
During the acoustic-model training stage, we employ the energy dip, zero crossing rate, and autocorrelation function to segment speech sounds. And use the MFCC (mel scale filter cepstral coefficient) to evaluate fea-ture parameters. Through the process of Binary splitting the vector quan-tization codebooks are found, the DHMM (Discrete Hidden Markov Models) is used to establish all acoustic-models, and the BaumWelch al-gorithm is chosen to adapt the optimal solution. On the recognition part, the Kohonon Network is used to calculate codeword sequence. The Beam search is used to replacement of Viterbi algorithm that gives the best re-sult of recognition in DHMM.
The recognition rates of speaker-independent experiments can reach up to 85.75%. It shows that the system has achieved good performance.
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author2 |
Chu-Kuei Tu |
author_facet |
Chu-Kuei Tu Jia-Hui Li 李佳慧 |
author |
Jia-Hui Li 李佳慧 |
spellingShingle |
Jia-Hui Li 李佳慧 Research of Speaker Independent Spoken MandarinSpoken Word Recognition System |
author_sort |
Jia-Hui Li |
title |
Research of Speaker Independent Spoken MandarinSpoken Word Recognition System |
title_short |
Research of Speaker Independent Spoken MandarinSpoken Word Recognition System |
title_full |
Research of Speaker Independent Spoken MandarinSpoken Word Recognition System |
title_fullStr |
Research of Speaker Independent Spoken MandarinSpoken Word Recognition System |
title_full_unstemmed |
Research of Speaker Independent Spoken MandarinSpoken Word Recognition System |
title_sort |
research of speaker independent spoken mandarinspoken word recognition system |
publishDate |
2001 |
url |
http://ndltd.ncl.edu.tw/handle/99112543444173635176 |
work_keys_str_mv |
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