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http://dx.doi.org/10.5370/KIEE.2016.65.1.116

Emotion Recognition Using Tone and Tempo Based on Voice for IoT  

Byun, Sung-Woo (Dept. of Computer Science, Sangmyung University)
Lee, Seok-Pil (Dept. of Media Software, Sangmyung Univerity)
Publication Information
The Transactions of The Korean Institute of Electrical Engineers / v.65, no.1, 2016 , pp. 116-121 More about this Journal
Abstract
In Internet of things (IoT) area, researches on recognizing human emotion are increasing recently. Generally, multi-modal features like facial images, bio-signals and voice signals are used for the emotion recognition. Among the multi-modal features, voice signals are the most convenient for acquisition. This paper proposes an emotion recognition method using tone and tempo based on voice. For this, we make voice databases from broadcasting media contents. Emotion recognition tests are carried out by extracted tone and tempo features from the voice databases. The result shows noticeable improvement of accuracy in comparison to conventional methods using only pitch.
Keywords
Emotion recognition; Speech; Tone; Tempo;
Citations & Related Records
Times Cited By KSCI : 4  (Citation Analysis)
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1 Chung-Hsien Wu, Wen-Li Wei, Jen-Chun Lin, Wei-Yu Lee "Speaking Effect Removal on Emotion Recognition From Facial Expressions Based on Eigenface Conversion", Multimedia, IEEE Transactions on, Vol. 15, pp. 1732-1744, July 2013.   DOI
2 Sung-Woo Byun, So-min Lee, Seok-Pil Lee, "A Selection of Optimal EEG Channel for Emotion Analysis According to Music Listening using Stochastic Variables", KIEE, Vol. 62, No. 11, pp. 1598-1603, November 2013.
3 So-min Lee, Sung-Woo Byun, Seok-Pil Lee, "Comparison of EEG Feature Vector for Emotion Classification according to Music Listening", KIEE, Vol. 63, No. 5, pp 696 - 702, May 2014.
4 Jung-In Lee, Hong-Goo Kang, "On the Importance of Tonal Features for Speech Emotion Recognition", JBE, Vol. 18, No. 5, pp. 713-721, September 2013.
5 Carlos Busso, Zhigang Deng, Serdar Yildirim, Murtaza Bulut, Chul Min Lee, Abe Kazemzadeh, Sungbok Lee, Ulrich Neumann, Shrikanth Narayanan, "Analysis of emotion recognition using facial expressions, speech and multimodal information", ICMI '04 Proceedings of the 6th international conference on Multimodal interfaces, pp. 205-211, October 2004.
6 Daniel Neiberg, Kjell Elenius, Kornel Laskowski, "Emotion Recognition in Spontaneous Speech Using GMMs", Proc. Int',l Conf. Spoken Language Processing (ICSLP ',06), pp. 809-812, 2006.
7 Xin Xu, Ya Li, Xiaoying Xu, Zhengqi Wen, Hao Che, Shanfeng Liu, Jianhua Tao, "Survey on discriminative feature selection for speech emotion recognition", Chinese Spoken Language Processing (ISCSLP), 2014 9th IEEE International Symposium on, pp. 345-349, 2014.
8 Vijayan, A.E, Sen, D, Sudheer, A.P, Hao Che, Shanfeng Liu, Jianhua Tao, "EEG-Based Emotion Recognition Using Statistical Measures and Auto-Regressive Modeling", Computational Intelligence & Communication Technology (CICT), 2015 IEEE International Conference on, pp. 587-591, 2015.
9 Sung-Woo Byun, Seok-Pil Lee, "A study on pitch detection for RUI emotion classification based on voice", 2015 Conference on The Korean Society Of Broad Engineers, pp. 421-424, July 2015.
10 Kostov, V, Fukuda, S, "Emotion in user interface, voice interaction system", Systems, Man, and Cybernetics, 2000 IEEE International Conference on, pp. 798-803, October 2000.
11 Guehyun Lee, Weon-Goo Kim, "Emotion Recognition using Pitch Parameters of Speech", KIISS, Vol. 25, No. 3, pp. 272-278, June 2015.
12 A. Ghosh, S. Devadas, K. Keutzer and J. White, "Estimation of Average Switching Activity in Combinational and Sequential Circuits," ACM/IEE Design Automation Conf., pp. 253-25.