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Conference Paper Construction of a Database of Emotional Speech Using Emotion Sounds from Movies and Dramas
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Authors
Youjung Ko, Insuk Hong, Hyunsoon Shin, Yoonjoong Kim
Issue Date
2017-06
Citation
International Conference on Information and Communications (ICIC) 2017, pp.1-2
Language
English
Type
Conference Paper
DOI
https://dx.doi.org/10.1109/INFOC.2017.8001672
Project Code
16HH3300, Development of Military Life Management System based on Emotion Recognition, Shin Hyun Soon
Abstract
In this study, an emotional speech database called Hanbat Emotional Database (HEMO) was constructed using movie and drama scenes in which emotion is abundantly expressed by professional actors. HEMO consists of 454 speech samples classified into seven emotion categories such as anger, happiness, sadness, disgust, surprise, fear, and neutral. In order to evaluate the performance of HEMO, consistent experiments were conducted based on HMM (Hidden Markov Model) and GMM (Gaussian Mixture Model) for both HEMO and the Berlin Emotional Speech Database (EMO). HEMO showed better results than EMO with a positive recognition rate of 78.89%.
KSP Keywords
Gaussian mixture Model(GMM), Positive recognition, Recognition rate, Speech Database, Speech samples, emotional speech, hidden Markov Model