Searching for just a few words should be enough to get started. If you need to make more complex queries, use the tips below to guide you.
Issue title: Special Section: Ambient advancements in intelligent computational sciences
Guest editors: Shailesh Tiwari, Munesh Trivedi and Mohan L. Kohle
Article type: Research Article
Authors: Gupta, Manish; * | Bharti, Shambhu Shankar | Agarwal, Suneeta
Affiliations: Department of Computer Science and Engineering, National Institute of Technology, Allahabad, UP, India
Correspondence: [*] Corresponding author. Manish Gupta, Department of Computer Science and Engineering, National Institute of Technology, Allahabad, U.P.- 211004, India. E-mail: [email protected].
Abstract: Emotion is a property by which human beings and machines can be differentiated as machines are emotionless while human beings are not. If the emotion of a speaker is recognized then others can interact accordingly. This paper presents a new approach for recognizing all the six basic emotions (Happy, anger, fear, sadness, boredom and neutral) from the speech signals more effectively. To recognize the emotion of a speaker, pitch value and two wavelet packet feature vectors derived from speech signals are used. Principal Component Analysis (PCA) has been applied to reduce the dimension of feature vectors. Random Forest (RF) and Support Vector Machine (SVM) classifiers are trained separately based on these reduced feature vectors. The experimental results show that the accuracy of emotion recognition with Random Forest classifier is 86.11% while with SVM classifier it is 84.41%. Experimentally, it is also found that clean speech of 1 sec duration is sufficient enough to recognize emotion of the speaker.
Keywords: Pitch, emotions, speech recognition, SVM, Random Forest (RF)
DOI: 10.3233/JIFS-169694
Journal: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 2, pp. 1541-1553, 2018
IOS Press, Inc.
6751 Tepper Drive
Clifton, VA 20124
USA
Tel: +1 703 830 6300
Fax: +1 703 830 2300
[email protected]
For editorial issues, like the status of your submitted paper or proposals, write to [email protected]
IOS Press
Nieuwe Hemweg 6B
1013 BG Amsterdam
The Netherlands
Tel: +31 20 688 3355
Fax: +31 20 687 0091
[email protected]
For editorial issues, permissions, book requests, submissions and proceedings, contact the Amsterdam office [email protected]
Inspirees International (China Office)
Ciyunsi Beili 207(CapitaLand), Bld 1, 7-901
100025, Beijing
China
Free service line: 400 661 8717
Fax: +86 10 8446 7947
[email protected]
For editorial issues, like the status of your submitted paper or proposals, write to [email protected]
如果您在出版方面需要帮助或有任何建, 件至: [email protected]