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Emotion Recognition Using Speech and EEG Signal ñA Review
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 15 - Number 3 |
| Year of Publication: 2011 |
| Authors: Priyanka Abhang, Shashibala Rao, Bharti W. Gawali, Pramod Rokade |
10.5120/1925-2570
|
Priyanka Abhang, Shashibala Rao, Bharti W. Gawali, Pramod Rokade . Emotion Recognition Using Speech and EEG Signal ñA Review. International Journal of Computer Applications. 15, 3 ( February 2011), 37-40. DOI=10.5120/1925-2570
Abstract
In recent years the research interest is improving in the field of human computer interaction. This paper focus on one of the aspect of human computer interaction in concern with, the recognition of emotion in a person with the help of Electroencephalogram (EEG) signals and speech. EEG uses an electrical activity of the neurons inside the brain. EEG machine is used for acquisition of the electrical potential generated by the neurons when they are active. The Brain cells communicate with each other by sending electrical impulses. Emotions allow people to express themselves beyond the verbal domain. Speech is the most natural form of communication. A much of work is been done in speech recognition in various languages. It is one of the components that closely related to emotions. Very less work has been carried out using combine aspects of speech, emotion and EEG. Thus this paper attempts to review the combine efforts of EEG brain signal and Speech to recognize the emotions in humans.
References
- Kazuhiko Takahashi, “Remarks on Emotion Recognition from Bio-Potential Signals” 2nd International Conference on Autonomous Robots and Agents December 13-15, 2004, Palmerston North, New Zealand,2004.
- Tsang-Long Pao, Yu-Ye Chen, Jun-Heng Yeh, Yuan-Hao Chang “Emotion Recognition and Evaluation of Mandarian Speech Using Weighted D-KNN Classification” Department of Computer Science and Engineering, Tatung University, Taipei.
- 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”, Viterbi School of Engineering, University of Southern California, Los Angeles.
- http://cslu.cse.ogi.edu/HLTsurvey/ch1node4.html
- http://www.bem.fi/book/13/13.htm
- Rafal Bogacz, Urszula Markowska-Kaczmar, Androzej Kozik, “ Blinking Artefact Recognition in EEG signal using Artificial Neural Network”, Computer Science and Management Department, Wroclaw.
- M.Ungureanu, C. Bigan, R. Strungaru, V.Lazarescu “Independent Component Analysis Applied in Biomedical Signal Processing”.Measurement Science Review, Volume 4,section 2, 2004
- Vijay Khare, Jayashree Santosh and Sneh Anand, “ Classification of EEG signals based on Neural Network to Discriminate Five Mental states” SPIT-IEEE colloquium and International Conference, Mumbai, India
- Kaushik Majumdar, Member IEEE, “Constraining Minimum-Norm Inverse by Phase Synchronization and Signal power of the scalp EEG channels”, IEEE Transactions of Biomedical engineering, Vol.56, No.4, April 2009.
- David R. Hardoon and John Shawe- Taylor, “Signal Extraction for Brain-Computer Interface”, Oct 9,2003.M. Young, The Techincal Writers Handbook. Mill Valley, CA: University Science, 1989
- Filipe Silva and Pablo Dias, “Brain-Computer Interface for navigating in virtual environments”, MAP-I doctoral programme, 2008-2009.3
- Ashkan Yazdani, Touradj Ebrahimi, Ulrich Hoffmann, “Classification of EEG signals using Dempster Shafer Theory and a K- Nearest Neighbor Classifier”, 4th International IEEE EMBS conference on Neural Engineering Turkey, April 29-May2,2009
- Lester Ingber, “Statistical mechanics of Neocortical Interactions: EEG Eigenfunction of short-term memory”, Chicago Mercantile Exchange Centre.
- Srinath Vukkadala, Vijaylakshmi.S and Vijayapriya.S, “Automated Detection of Epileptic EEG using Approximate Entropy In Elman networks”, International Journal of Recent Trends in Engineering”, Vol1,No.1, May2009.
- Vitaly Schetinin, “Polynomial Neural Networks Learnt to classify EEG signals”, NIMIA-SC2001-2001, Measurement and Related Industrial Applications: Studycases Crema,9-20 Oct 2001
- Rafal Bogacz, URSZULA Markowska- Kaczmar, Androzej Korik, “Blinking Artefact Recognition in EEG signal using Artificial Neural Network”, Computer Science and Management Department, Wroclaw.G. R. Faulhaber, “Design of service systems with priority reservation,” in Conf. Rec. 1995 IEEE Int. Conf. Communications, pp. 3–8.
- M.A. Anusuya, S.K.Katti, “Speech Recognition BY machine: A Review”, Department of Computer Science and Engineering, Mysore, International Journal of Computer Science and Information Society, Vol.6.No.3, 2009
- WANG Dong, CHEN Yi-Ning, LIU Jia “ An Algorithm for Voiced/ Unvoiced decision and pitch estimation in speech feature extraction” ,Department of Electronical Engineering, Beijing.
- Robert Horlings, “Emotion recognition using brain activity”, Man-Machine Interaction Group TU Delft,27 March 2008.
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