Improved Filter-bank of Speech Feature Coefficient Extraction
碩士 === 國立中央大學 === 電機工程學系 === 103 === The theme of this thesis is to improve the part of feature extraction in the speech keyword recognition. In the framework of the entire keyword recognition system, feature extraction is to highlight the individual features of different voices, and can reduce th...
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Format: | Others |
Language: | zh-TW |
Published: |
2015
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Online Access: | http://ndltd.ncl.edu.tw/handle/46443189430807779003 |
Summary: | 碩士 === 國立中央大學 === 電機工程學系 === 103 === The theme of this thesis is to improve the part of feature extraction in the speech keyword recognition. In the framework of the entire keyword recognition system, feature extraction is to highlight the individual features of different voices, and can reduce the amount of data by means of the extract process. Many researchers have presented different ways to extract the speech features in the literature, or on which making improvements at extracting feature coefficient method.
This thesis discusses several improved filter bank in mel-frequency cepstral coefficients (MFCC). The best filter bank is used to replace the original mel-triangular filter set. The experimental results showed that the application of this improved filter bank can effectively improve the recognition rate of the keyword extraction system.
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