Abstract
In this paper, we introduce a practical spoken dialogue interface for intelligent TV based on goal-oriented dialogue modeling. It uses a frame structure for representing the user intention and determining the next action. To analyze discourse context, we employ several statistical learning techniques and device an incremental dialogue strategy learning method from training corpus. By empirical experiments, we demonstrated the efficiency of the proposed system. In case of the subjective evaluation, we obtained 73% user satisfaction ratio, while the objective evaluation result was over 90% in case of a restricted situation for commercialization.
This work was supported by the IT R&D program of MIC/IITA. [2006-S036-01, Development of large vocabulary/interactive distributed/embedded VUI for new growth engine industries].
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Zue, V., Seneff, S., Glass, J.R., Polifroni, J., Pao, C., Hazen, T.J., Hetherington, L.: JUPITER: A Telephone-Based Conversational Interface for Weather Information. IEEE Transactions on Speech and Audio Processing 8(1), 85–96 (2000)
Fujita, Keiko, Kuwano, Hiroyasu, Tsuzuki, Takashi, Ono, Yoshio, Ishihara, Toshihide: A New Digital TV Interface Employing Speech Recognition. IEEE Transactions on Consumer Electronics 49(3), 765–769 (2003)
Ardissono, L., Kobsa, A., Maybury, M.: Personalized Digital Television: Targeting Programs to Individual Viewers. Kluwer Academic Publishers, Dordrecht (2004)
Park, J., Lee, S., Kim, S.: Keyword Spotting for Far-field Speech Input by Categorical Fillers and Speech Enhancement. In: The Proceedings of 22nd Speech Communication and Signal Processing (2005)
Lee, Changki, Eun, Jihyun, Jeong, Minwoo, Lee, Geunbae, G., Hwang, Yi-Gyu, Jang, Myung-Gil: AÂ Multi-Strategic Concept-Spotting Approach for Robust Spoken Korean Understanding, ETRI Journal, 29(2) (2007)
Chu-Carroll, Jennifer: MIMIC: An Adaptive Mixed Initiative Spoken Dialogue System for Information Queries. In: Christodoulakis, D.N. (ed.) NLP 2000. LNCS (LNAI), vol. 1835, pp. 97–104. Springer, Heidelberg (2000)
Kim, Harksoo, Cho, Jeong-Mi, Seo, Jungyun.: Anaphora Resolution Using an Extended Centering Algorithm in a Multi-modal Dialogue System. In: The proceedings of the Workshop on the Relation of Discourse/Dialogue Structure and reference (1999)
Gangardiwala, A., Polikar, R.: Dynamically Weighted Majority Voting for Incremental Learning and Comparison of Three Boosting Based Approaches. In: The proceeding of IJCNN, pp. 1131–1136 (2005)
Minker, Wolfgan.: Evaluation Methodologies for Interactive Speech Systems. In: The proceedings of LREC 1998, pp. 199–206 (1998)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2007 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Oh, HJ., Lee, CH., Hwang, YG., Jang, MG. (2007). Dialogue Management for Intelligent TV Based on Statistical Learning Method. In: Matoušek, V., Mautner, P. (eds) Text, Speech and Dialogue. TSD 2007. Lecture Notes in Computer Science(), vol 4629. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74628-7_83
Download citation
DOI: https://doi.org/10.1007/978-3-540-74628-7_83
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-74627-0
Online ISBN: 978-3-540-74628-7
eBook Packages: Computer ScienceComputer Science (R0)