A Research of Speech Emotion Recognition Based on Deep Belief Network and SVM
Joint Authors
Feng, Dongyu
Fu, Wenlong
Gong, Wei
Huang, Chenchen
Source
Mathematical Problems in Engineering
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-7, 7 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-08-12
Country of Publication
Egypt
No. of Pages
7
Main Subjects
Abstract EN
Feature extraction is a very important part in speech emotion recognition, and in allusion to feature extraction in speech emotion recognition problems, this paper proposed a new method of feature extraction, using DBNs in DNN to extract emotional features in speech signal automatically.
By training a 5 layers depth DBNs, to extract speech emotion feature and incorporate multiple consecutive frames to form a high dimensional feature.
The features after training in DBNs were the input of nonlinear SVM classifier, and finally speech emotion recognition multiple classifier system was achieved.
The speech emotion recognition rate of the system reached 86.5%, which was 7% higher than the original method.
American Psychological Association (APA)
Huang, Chenchen& Gong, Wei& Fu, Wenlong& Feng, Dongyu. 2014. A Research of Speech Emotion Recognition Based on Deep Belief Network and SVM. Mathematical Problems in Engineering،Vol. 2014, no. 2014, pp.1-7.
https://search.emarefa.net/detail/BIM-495695
Modern Language Association (MLA)
Huang, Chenchen…[et al.]. A Research of Speech Emotion Recognition Based on Deep Belief Network and SVM. Mathematical Problems in Engineering No. 2014 (2014), pp.1-7.
https://search.emarefa.net/detail/BIM-495695
American Medical Association (AMA)
Huang, Chenchen& Gong, Wei& Fu, Wenlong& Feng, Dongyu. A Research of Speech Emotion Recognition Based on Deep Belief Network and SVM. Mathematical Problems in Engineering. 2014. Vol. 2014, no. 2014, pp.1-7.
https://search.emarefa.net/detail/BIM-495695
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-495695