Burmese speech word recognition
The aim of this study is to develop a Burmese speech word recognition system. A phone level (sub-word) based voice-operated interface for phone dialing system is implemented using the Hidden Markov Model Tool Kit (HTK). The Mel Frequency Cepstral Coefficients (MFCCs) and Perceptual Linear Predictio...
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sg-ntu-dr.10356-414212023-07-04T15:29:28Z Burmese speech word recognition Zaw, Wai Phyo Soon Ing Yann School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering::Electronic systems::Signal processing The aim of this study is to develop a Burmese speech word recognition system. A phone level (sub-word) based voice-operated interface for phone dialing system is implemented using the Hidden Markov Model Tool Kit (HTK). The Mel Frequency Cepstral Coefficients (MFCCs) and Perceptual Linear Prediction Cepstral Coefficients (PLPCCs) are employed as feature in this project. In this study, the method called Half-Wave Rectification is applied to the MFCC to enhance the spectral peaks. The recognizer is evaluated with MFCCs and PLPCCs as well as rectified MFCCs. The evaluated results are discussed and finally, this study also provides the recommendation and future works to extend this project. Master of Science (Signal Processing) 2010-07-02T08:21:05Z 2010-07-02T08:21:05Z 2008 2008 Thesis http://hdl.handle.net/10356/41421 en 75 p. application/pdf |
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DRNTU::Engineering::Electrical and electronic engineering::Electronic systems::Signal processing Zaw, Wai Phyo Burmese speech word recognition |
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The aim of this study is to develop a Burmese speech word recognition system. A phone level (sub-word) based voice-operated interface for phone dialing system is implemented using the Hidden Markov Model Tool Kit (HTK). The Mel Frequency Cepstral
Coefficients (MFCCs) and Perceptual Linear Prediction Cepstral Coefficients (PLPCCs)
are employed as feature in this project. In this study, the method called Half-Wave
Rectification is applied to the MFCC to enhance the spectral peaks. The recognizer is
evaluated with MFCCs and PLPCCs as well as rectified MFCCs. The evaluated results
are discussed and finally, this study also provides the recommendation and future works
to extend this project. |
author2 |
Soon Ing Yann |
author_facet |
Soon Ing Yann Zaw, Wai Phyo |
format |
Theses and Dissertations |
author |
Zaw, Wai Phyo |
author_sort |
Zaw, Wai Phyo |
title |
Burmese speech word recognition |
title_short |
Burmese speech word recognition |
title_full |
Burmese speech word recognition |
title_fullStr |
Burmese speech word recognition |
title_full_unstemmed |
Burmese speech word recognition |
title_sort |
burmese speech word recognition |
publishDate |
2010 |
url |
http://hdl.handle.net/10356/41421 |
_version_ |
1772827291581153280 |