Random Deep Belief Networks for Recognizing Emotions from Speech Signals
Joint Authors
Wen, Gui-Hua
Li, Huihui
Huang, Jubing
Li, Danyang
Xun, Eryang
Source
Computational Intelligence and Neuroscience
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-03-05
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Abstract EN
Now the human emotions can be recognized from speech signals using machine learning methods; however, they are challenged by the lower recognition accuracies in real applications due to lack of the rich representation ability.
Deep belief networks (DBN) can automatically discover the multiple levels of representations in speech signals.
To make full of its advantages, this paper presents an ensemble of random deep belief networks (RDBN) method for speech emotion recognition.
It firstly extracts the low level features of the input speech signal and then applies them to construct lots of random subspaces.
Each random subspace is then provided for DBN to yield the higher level features as the input of the classifier to output an emotion label.
All outputted emotion labels are then fused through the majority voting to decide the final emotion label for the input speech signal.
The conducted experimental results on benchmark speech emotion databases show that RDBN has better accuracy than the compared methods for speech emotion recognition.
American Psychological Association (APA)
Wen, Gui-Hua& Li, Huihui& Huang, Jubing& Li, Danyang& Xun, Eryang. 2017. Random Deep Belief Networks for Recognizing Emotions from Speech Signals. Computational Intelligence and Neuroscience،Vol. 2017, no. 2017, pp.1-9.
https://search.emarefa.net/detail/BIM-1139846
Modern Language Association (MLA)
Wen, Gui-Hua…[et al.]. Random Deep Belief Networks for Recognizing Emotions from Speech Signals. Computational Intelligence and Neuroscience No. 2017 (2017), pp.1-9.
https://search.emarefa.net/detail/BIM-1139846
American Medical Association (AMA)
Wen, Gui-Hua& Li, Huihui& Huang, Jubing& Li, Danyang& Xun, Eryang. Random Deep Belief Networks for Recognizing Emotions from Speech Signals. Computational Intelligence and Neuroscience. 2017. Vol. 2017, no. 2017, pp.1-9.
https://search.emarefa.net/detail/BIM-1139846
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1139846