A new hybrid PSO assisted biogeography-based optimization for emotion and stress recognition from speech signal
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- 作者：Yogesh C.K.a ; yyogesh61@gmail.com" class="auth_mail" title="E-mail the corresponding author ; M. Hariharanb ; hari@unimap.edu.my" class="auth_mail" title="E-mail the corresponding author ; Ruzelita Ngadirana ; ruzelita@unimap.edu.my" class="auth_mail" title="E-mail the corresponding author ; Abdul Hamid Adomb ; dhamid@unimap.edu.my" class="auth_mail" title="E-mail the corresponding author ; Sazali Yaacobc ; sazali.yaacob@unikl.edu.my" class="auth_mail" title="E-mail the corresponding author ; Chawki Berkaib ; chawki.berkai@gmail.com" class="auth_mail" title="E-mail the corresponding author ; Kemal Polatd ; kpolat@ibu.edu.tr" class="auth_mail" title="E-mail the corresponding author
- 关键词：Speech signals ; Emotions ; Feature extraction ; Feature selection and emotion recognition
- 刊名：Expert Systems with Applications
- 出版年：2017
- 出版时间：1 March 2017
- 年：2017
- 卷：69
- 期：Complete
- 页码：149-158
- 全文大小：633 K
文摘
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OSBSBCFs were used for multiclass emotion/stress recognition from speech signal.
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A New Hybrid PSO Assisted BBO (PSOBBO) was proposed for feature selection.
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Simulations were conducted for three speech emotion and also validated using eight benchmark datasets.
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The best prediction performances were achieved for the simulations conducted.