Abstract
As conversation system it must converse with various users and have to talk about various conversations, so we have to prepare large numbers of information for conversation knowledge database, but it is so especially difficult for us. The wealth of information on the web is full and quick so those make it an attractive resource for seeking quick information to simple. Recognizing a human’s emotional state can be helpful in various contexts. The most promising one is probably the man-machine interaction, the communication between an assisting robot in the household and its human user. In this paper we present an experiment named an emotion recognition conversation system based on knowledge database automatic architecture. In this exploration there are two parts different than the generic conversation system. First, our conversation system can automatic construct of knowledge database base on the Really Simple Syndication parse. Second, this system can recognize emotion from the conversation contents. The experiment showed that this method could achieve better results in practice.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
James, F.A., Byron, D.K., Dzikovska, M., Ferguson, G., Galescu, L., Stent, A.: Towards Conversational Human-Computer Interaction. AI Magazine (2001)
Cowie, R., Douglas-Cowie, E., Tsapatsoulis, N., Votsis, G., Kollias, S., Fellenz, W., Taylor, J.G.: Emotion recognition in human-computer interaction. IEEE Sig. Proc. Mag. 18(1), 32–80 (2001)
Cf: http://www.clopinet.com/isabelle/Projects/SVM/applist.html
Vapnik, V.: Statistical Learning Thoery. Wiley, Chichester (1998)
Cristianini, N., Shaw, J.: E-Taylor. An Introduction to Support Vector Machines and other Kernel-based Learning Methods. Cambridge University Press, Cambridge (to appear)
Chang, C.C., Lin, C.J.: LIBSVM: A Library for Support Vector Machines (2001), Software available at http://www.csie.ntu.edu.tw/~cjlin/libsvm
Teng, Z., Ren, F.J., Kuroiwa, S.: Recognition of Emotion with SVMs. In: Huang, D.-S., Li, K., Irwin, G.W. (eds.) ICIC 2006. LNCS (LNAI), vol. 4114, pp. 701–710. Springer, Heidelberg (2006)
Billerbeck, B., Zobel, J.: Techniques for Efficient Query Expansion
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2007 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Teng, Z., Ren, F., Kuroiwa, S. (2007). An Emotion Recognition Conversation System Based on Knowledge Database Automatic Architecture. In: Huang, DS., Heutte, L., Loog, M. (eds) Advanced Intelligent Computing Theories and Applications. With Aspects of Contemporary Intelligent Computing Techniques. ICIC 2007. Communications in Computer and Information Science, vol 2. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74282-1_81
Download citation
DOI: https://doi.org/10.1007/978-3-540-74282-1_81
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-74281-4
Online ISBN: 978-3-540-74282-1
eBook Packages: Computer ScienceComputer Science (R0)