DocumentCode :
2269254
Title :
Speech emotion recognition based on supervised locally linear embedding
Author :
Zhang, Shiqing ; Li, Lemin ; Zhao, Zhijin
Author_Institution :
Sch. of Commun. & Inf. Eng., Univ. of Electron. Sci. & Technol. of China, Chengdu, China
fYear :
2010
fDate :
28-30 July 2010
Firstpage :
401
Lastpage :
404
Abstract :
Speech emotion recognition is a new and challenging subject in signal processing area. In this paper, a new feature extraction method based on supervised locally linear embedding (SLLE) is proposed for speech emotion recognition. SLLE is used to implement nonlinear dimensionality reduction on high-dimensional emotional speech features with nonlinear manifold structure. And then the enhanced low-dimensional data representations embedded with SLLE are extracted for speech emotion recognition. Experimental results on natural emotional Chinese speech database confirm the validity and high performance of the proposed method.
Keywords :
data structures; emotion recognition; feature extraction; signal processing; speech recognition; data representations; feature extraction; high-dimensional emotional speech features; natural emotional Chinese speech database; nonlinear manifold structure; signal processing; speech emotion recognition; supervised locally linear embedding; Feature extraction; Principal component analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Communications, Circuits and Systems (ICCCAS), 2010 International Conference on
Conference_Location :
Chengdu
Print_ISBN :
978-1-4244-8224-5
Type :
conf
DOI :
10.1109/ICCCAS.2010.5581962
Filename :
5581962
Link To Document :
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