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Pattern Recognition Methods and Features Selection for Speech Emotion Recognition System
Joint Authors
Voznak, Miroslav
Partila, Pavol
Tovarek, Jaromir
Source
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-7, 7 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-08-04
Country of Publication
Egypt
No. of Pages
7
Main Subjects
Medicine
Information Technology and Computer Science
Abstract EN
The impact of the classification method and features selection for the speech emotion recognition accuracy is discussed in this paper.
Selecting the correct parameters in combination with the classifier is an important part of reducing the complexity of system computing.
This step is necessary especially for systems that will be deployed in real-time applications.
The reason for the development and improvement of speech emotion recognition systems is wide usability in nowadays automatic voice controlled systems.
Berlin database of emotional recordings was used in this experiment.
Classification accuracy of artificial neural networks, k-nearest neighbours, and Gaussian mixture model is measured considering the selection of prosodic, spectral, and voice quality features.
The purpose was to find an optimal combination of methods and group of features for stress detection in human speech.
The research contribution lies in the design of the speech emotion recognition system due to its accuracy and efficiency.
American Psychological Association (APA)
Partila, Pavol& Voznak, Miroslav& Tovarek, Jaromir. 2015. Pattern Recognition Methods and Features Selection for Speech Emotion Recognition System. The Scientific World Journal،Vol. 2015, no. 2015, pp.1-7.
https://search.emarefa.net/detail/BIM-1078896
Modern Language Association (MLA)
Partila, Pavol…[et al.]. Pattern Recognition Methods and Features Selection for Speech Emotion Recognition System. The Scientific World Journal No. 2015 (2015), pp.1-7.
https://search.emarefa.net/detail/BIM-1078896
American Medical Association (AMA)
Partila, Pavol& Voznak, Miroslav& Tovarek, Jaromir. Pattern Recognition Methods and Features Selection for Speech Emotion Recognition System. The Scientific World Journal. 2015. Vol. 2015, no. 2015, pp.1-7.
https://search.emarefa.net/detail/BIM-1078896
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1078896