Gender dependent word-level emotion detection using global spectral speech features
In this study, global spectral features extracted from word and sentence levels are studied for speech emotion recognition. MFCC (Mel Frequency Cepstral Coefficient) were used as spectral information for recognition purpose. Global spectral features representing gross statistics such as mean of MFCC...
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| Main Author: | |
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| Format: | Thesis |
| Language: | English English |
| Published: |
2015
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| Subjects: | |
| Online Access: | http://etd.uum.edu.my/4518/ |
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