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A Robust Method for Speech Emotion Recognition Based on Infinite Student’s t -Mixture Model
Joint Authors
Zha, Cheng
Zhao, Li
Zhang, Xinran
Tao, Huawei
Xu, Xinzhou
Source
Mathematical Problems in Engineering
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-10-07
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
Speech emotion classification method, proposed in this paper, is based on Student’s t -mixture model with infinite component number (iSMM) and can directly conduct effective recognition for various kinds of speech emotion samples.
Compared with the traditional GMM (Gaussian mixture model), speech emotion model based on Student’s t -mixture can effectively handle speech sample outliers that exist in the emotion feature space.
Moreover, t -mixture model could keep robust to atypical emotion test data.
In allusion to the high data complexity caused by high-dimensional space and the problem of insufficient training samples, a global latent space is joined to emotion model.
Such an approach makes the number of components divided infinite and forms an iSMM emotion model, which can automatically determine the best number of components with lower complexity to complete various kinds of emotion characteristics data classification.
Conducted over one spontaneous (FAU Aibo Emotion Corpus) and two acting (DES and EMO-DB) universal speech emotion databases which have high-dimensional feature samples and diversiform data distributions, the iSMM maintains better recognition performance than the comparisons.
Thus, the effectiveness and generalization to the high-dimensional data and the outliers are verified.
Hereby, the iSMM emotion model is verified as a robust method with the validity and generalization to outliers and high-dimensional emotion characters.
American Psychological Association (APA)
Zhang, Xinran& Tao, Huawei& Zha, Cheng& Xu, Xinzhou& Zhao, Li. 2015. A Robust Method for Speech Emotion Recognition Based on Infinite Student’s t -Mixture Model. Mathematical Problems in Engineering،Vol. 2015, no. 2015, pp.1-10.
https://search.emarefa.net/detail/BIM-1073922
Modern Language Association (MLA)
Zhang, Xinran…[et al.]. A Robust Method for Speech Emotion Recognition Based on Infinite Student’s t -Mixture Model. Mathematical Problems in Engineering No. 2015 (2015), pp.1-10.
https://search.emarefa.net/detail/BIM-1073922
American Medical Association (AMA)
Zhang, Xinran& Tao, Huawei& Zha, Cheng& Xu, Xinzhou& Zhao, Li. A Robust Method for Speech Emotion Recognition Based on Infinite Student’s t -Mixture Model. Mathematical Problems in Engineering. 2015. Vol. 2015, no. 2015, pp.1-10.
https://search.emarefa.net/detail/BIM-1073922
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1073922