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Speaker-independent speech emotion recognition by fusion of functional and accompanying paralanguage features
- Speaker-independent speech emotion recognition by fusion of functional and accompanying paralanguage features
- Frontiers of Information Technology & Electronic Engineering Vol. 14, Issue 7, Pages: 573-582(2013)
- Affiliations：
Department of Computer Science and Communication Engineering, Jiangsu University, Zhenjiang 212013, China
- Author bio：
[ "Qi-rong MAO, E-mail: mao_qr@ujs.edu.cn" ]
- Funds：
DOI：10.1631/jzus.CIDE1310
CLC： TP391.4Received：29 December 2012，
Revised：2013-06-06，
Published：2013-07
- Accepted：
Scan QR Code
MAO Qi-rong, ZHAO Xiao-lei, HUANG Zheng-wei, et al. Speaker-independent speech emotion recognition by fusion of functional and accompanying paralanguage features[J]. Frontiers of Information Technology & Electronic Engineering, 2013, 14(7): 573-582.
MAO Qi-rong, ZHAO Xiao-lei, HUANG Zheng-wei, et al. Speaker-independent speech emotion recognition by fusion of functional and accompanying paralanguage features[J]. Frontiers of Information Technology & Electronic Engineering, 2013, 14(7): 573-582. DOI： 10.1631/jzus.CIDE1310.
摘要
Abstract
Functional paralanguage includes considerable emotion information
and it is insensitive to speaker changes. To improve the emotion recognition accuracy under the condition of speaker-independence
a fusion method combining the functional paralanguage features with the accompanying paralanguage features is proposed for the speaker-independent speech emotion recognition. Using this method
the functional paralanguages
such as laughter
cry
and sigh
are used to assist speech emotion recognition. The contributions of our work are threefold. First
one emotional speech database including six kinds of functional paralanguage and six typical emotions were recorded by our research group. Second
the functional paralanguage is put forward to recognize the speech emotions combined with the accompanying paralanguage features. Third
a fusion algorithm based on confidences and probabilities is proposed to combine the functional paralanguage features with the accompanying paralanguage features for speech emotion recognition. We evaluate the usefulness of the functional paralanguage features and the fusion algorithm in terms of precision
recall
and F1-measurement on the emotional speech database recorded by our research group. The overall recognition accuracy achieved for six emotions is over 67% in the speaker-independent condition using the functional paralanguage features.
关键词
Keywords
references
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