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KMID : 1022420170090020077
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Phonetics and Speech Sciences
2017 Volume.9 No. 2 p.77 ~ p.83
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Improved speech emotion recognition using histogram equalization and data augmentation techniques
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Heo Woon-Haeng
Kwon Oh-Wook
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Abstract
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We propose a new method to reduce emotion recognition errors caused by variation in speaker characteristics and speech rate. Firstly, for reducing variation in speaker characteristics, we adjust features from a test speaker to fit the distribution of all training data by using the histogram equalization (HE) algorithm. Secondly, for dealing with variation in speech rate, we augment the training data with speech generated in various speech rates. In computer experiments using EMO-DB, KRN-DB and eNTERFACE-DB, the proposed method is shown to improve weighted accuracy relatively by 34.7%, 23.7% and 28.1%, respectively.
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KEYWORD
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emotion recognition, histogram equalization, data augmentation
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