Gender dependent word-level emotion detection using global spectral speech features

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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书目详细资料
主要作者:	Siddique, Haris
格式:	Thesis
语言:	eng eng
出版:	2015
主题:	QA75 Electronic computers Computer science
在线阅读:	https://etd.uum.edu.my/4518/1/s814534.pdf https://etd.uum.edu.my/4518/2/s814534_abstract.pdf
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