NDLI: Novel feature extraction technique for child emotion recognition

Content Provider	IEEE Xplore Digital Library
Author	Palo, H.K. Mohanty, M.N. Chandra, M.
Copyright Year	2015
Description	Author affiliation: Dept. of Electron. & Commun. Eng., Siksha `O' Anusandhan Univ., Bhubaneswar, India (Palo, H.K.; Mohanty, M.N.) \|\| Dept. of Electron. & Commun. Eng., Birla Inst. of Technol., Ranchi, India (Chandra, M.)
Abstract	Human nature is unpredictable. It depends on his/her moods that relates to emotion. Emotion is a complex physiological characteristic of human being. It is highly flexible in case of children. An effective human-computer-interaction system is essential for such recognition. With fewer features effective recognition system design is still a challenge. In this paper, authors have been taken an attempt for it with child emotion. Feature extraction and its reduction are emphasized in this work. Initially Hurst parameters are used for feature extraction purpose. Next to it a novel method has been proposed as LP-VQC and is compared using Multi Layer Perceptron (MLP) network. The proposed technique has been shown as reduced feature set and with this feature set the recognition shows its effectiveness up to 80%. The comparison result shows the efficacy.
Starting Page	1
Ending Page	5
File Size	242327
Page Count	5
File Format	PDF
ISBN	9781479976768
e-ISBN	9781479976782
DOI	10.1109/EESCO.2015.7253839
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-01-24
Publisher Place	India
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Support vector machines MLP Emotion recognition Time-frequency analysis Accuracy LP-VQC Speech recognition Child Emotion Feature Extraction Feature extraction Speech Hurst parameter (pH)
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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