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A data-oriented approach to integrate emotions in adaptive dialogue management

Published: 28 January 2007 Publication History

Abstract

During the past years the involvement of emotions in dialogue design has attracted much interest in current research on intelligent human-computer interfaces. We focus on the implementation of a flexible and robust dialogue system which integrates emotions and other influencing parameters in the dialogue flow. In order to achieve a higher degree of adaptability we propose a simplified stochastic approach to model the dialogue manager's behavior based on the user's input and dialogue-influencing parameters like emotions.

References

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E. Levin, R. Pieraccini, and W. Eckert. A stochastic model of human machine interaction for learning dialog strategies. IEEE Transactions on Speech and Audio Processing, 8(1):11--23, January 2000.
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D. J. Litman, M. S. Kearns, S. B. Singh, and M. A. Walker. Automatic optimization of dialogue management. In Proceedings of the 17th Conference on Computational Linguistics, pages 502--508, 2000.
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D. J. Litman and S. Pan. Designing and Evaluating an Adaptive Spoken Dialogue System. User Modeling and User-Adapted Interaction, 12:111--137, 2002.
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A. Pittermann and J. Pittermann. Getting Bored with HTK? Using HMMs for Emotion Recognition. In 8th International Conference on Signal Processing (ICSP), volume 1, pages 704--707, Guilin, China, November 2006.
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N. Roy, J. Pineau, and S. Thrun. Spoken dialogue management using probabilistic reasoning. In Proceedings of the 38th Annual Meeting of the Association for Computational Linguistics (ACL2000), 2000.
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Cited By

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  • (2019)Interface feature prioritization for web servicesComputers in Human Behavior10.1016/j.chb.2008.12.02825:4(862-877)Online publication date: 10-Dec-2019
  • (2019)Collaborative Meaning Construction in Socioenactive Systems: Study with the mBotLearning and Collaboration Technologies. Designing Learning Experiences10.1007/978-3-030-21814-0_18(237-255)Online publication date: 15-Jun-2019
  • (2010)Emotion recognition and adaptation in spoken dialogue systemsInternational Journal of Speech Technology10.1007/s10772-010-9068-y13:1(49-60)Online publication date: 9-Mar-2010
  • Show More Cited By

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cover image ACM Conferences
IUI '07: Proceedings of the 12th international conference on Intelligent user interfaces
January 2007
388 pages
ISBN:1595934812
DOI:10.1145/1216295
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

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Publication History

Published: 28 January 2007

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Author Tags

  1. dialogue management
  2. human-computer interaction
  3. stochastic modeling

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Overall Acceptance Rate 746 of 2,811 submissions, 27%

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Cited By

View all
  • (2019)Interface feature prioritization for web servicesComputers in Human Behavior10.1016/j.chb.2008.12.02825:4(862-877)Online publication date: 10-Dec-2019
  • (2019)Collaborative Meaning Construction in Socioenactive Systems: Study with the mBotLearning and Collaboration Technologies. Designing Learning Experiences10.1007/978-3-030-21814-0_18(237-255)Online publication date: 15-Jun-2019
  • (2010)Emotion recognition and adaptation in spoken dialogue systemsInternational Journal of Speech Technology10.1007/s10772-010-9068-y13:1(49-60)Online publication date: 9-Mar-2010
  • (2009)Challenges in speech-based human–computer interfacesInternational Journal of Speech Technology10.1007/s10772-009-9023-y10:2-3(109-119)Online publication date: 10-Mar-2009

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