Li Zhang
ABSTRACT
We report new developments on affect detection from textual metaphorical affective expression and affect sensing from speech. The textual affect detection component has been embedded in an intelligent conversational AI agent interacting with human users under loose scenarios. The detected affective states from text also play an important role in producing emotional animation for users' avatars. Evaluation of the affect detection from speech and text is provided. Our work contributes to the conference themes on affective computing and ambient intelligence, human-robots interaction, multimodal interaction, narrative storytelling in education and evaluation of affective social interaction.
- Amir, N and Cohen. R. 2007. Characterizing Emotion in the Soundtrack of an Animated Film: Credible or Incredible? In Proceedings of ACII 2007, ACM, Springer, 148--158. Google Scholar
Digital Library
- ATT-Meta Project Databank: Examples of Usage of Metaphors of Mind. July 2008. http://www.cs.bham.ac.uk/~jab/ATT-Meta/Databank/.Google Scholar
- Aylett, R., Louchart, S., Dias, J., Paiva, A., Vala M., Woods, S. Hall, L. E. 2006. Unscripted Narrative for Affectively Driven Characters. IEEE Computer Graphics and Applications 26(3). 42--52. Google ScholarDigital Library
- Boucouvalas, A. C. 2002. Real Time Text-to-Emotion Engine for Expressive Internet Communications. In Being There: Concepts, Effects and Measurement of User Presence in Synthetic Environments. G. Riva, F. Davide and W. IJsselsteijn (eds.), 305--318.Google Scholar
- Cavazza, M., Smith, C., Charlton, D., Zhang, L., Turunen, M. and Hakulinen, J. 2008. A 'Companion' ECA with Planning and Activity Modelling. In Proceedings of AAMAS'08. Portugal, 1281--1284. Google ScholarDigital Library
- Cichosz, J. and Slot, K. 2007. Emotion recognition in speech signal using emotion-extracting binary decision trees. Doctoral Consortium. ACII 2007, ACM, Springer.Google Scholar
- Craggs, R. & Wood. M. 2004. A Two Dimensional Annotation Scheme for Emotion in Dialogue. In Proceedings of AAAI Spring Symposium: Exploring Attitude and Affect in Text.Google Scholar
- Egges, A., Kshirsagar, S. & Magnenat-Thalmann, N. 2003. A Model for Personality and Emotion Simulation, In Proceedings of Knowledge-Based Intelligent Information & Engineering Systems (KES2003), Lecture Notes in AI. Springer-Verlag: Berlin, 453--461.Google ScholarCross Ref
- Elliott, C., Rickel, J. & Lester, J. 1997. Integrating Affective Computing into Animated Tutoring Agents. In Proceedings of IJCAI'97 Workshop on Intelligent Interface Agents, 113--121.Google Scholar
- Glynn, D. 2002. Love and Anger. The grammatical structure of conceptual metaphors. Cognitive Approaches to Metaphor. Style 36: 541--559.Google Scholar
- Grimm, M., Kroschel, K., Harris, H., Nass, C., Schuller, B., Rigoll, G. and Moosmayr, T. 2007. On the Necessity and Feasibility of Detecting a Driver's Emotional State While Driving. In Proceedings of ACII 2007, Lisbon, ACM, Springer, 126--138. Google ScholarDigital Library
- Kövecses, Z. 1998. Are There Any Emotion-Specific Metaphors? In Speaking of Emotions: Conceptualization and Expression. Berlin and New York: Mouton de Gruyter, 127--151.Google Scholar
- Liu, H. & Singh, P. 2004. ConceptNet: A practical commonsense reasoning toolkit. BT Technology Journal, Volume 22, Kluwer Academic Publishers. Google ScholarDigital Library
- Mateas, M. 2002. Ph.D. Thesis. Interactive Drama, Art and Artificial Intelligence. School of Computer Science, Carnegie Mellon University. Google ScholarDigital Library
- Murray, I. R. and Arnott, J. L. 1995. Implementation and testing of a system for producing emotion-by-rule in synthetic speech. Speech Communication (16), 369--390. Google ScholarDigital Library
- Nogueiras, A., Moreno, A., Bonafante, A. and Maririo. J. 2001. Speech Emotion Recognition Using Hidden Markov Models, Eurospeech 2001, 2679--2682.Google ScholarCross Ref
- Oudeyer, P. Y. 2003. The production and recognition of emotions in speech: features and algorithms, International Journal in Human-Computer Studies, vol. 59/1--2, 157--183, Special Issue on Affective Computing. Google ScholarDigital Library
- Rayson, P. 2003. Matrix: A statistical method and software tool for linguistic analysis through corpus comparison. Ph.D. thesis, Lancaster University.Google Scholar
- Shaikh, M. A. M., Prendinger, H. & Mitsuru, I. 2007. Assessing sentiment of text by semantic dependency and contextual valence analysis. In Proceeding of ACII. Google ScholarDigital Library
- Zhang, L., Barnden, J. A., Hendley, R. J., Lee, M. G., Wallington, A. M. and Wen, Z. 2008. Affect Detection and Metaphor in E-drama. Int. J. Continuing Engineering Education and Life-Long Learning, Vol 18(2), 234--252.Google ScholarCross Ref
- Zhe, X. & Boucouvalas, A. C. 2002. Text-to-Emotion Engine for Real Time Internet Communication. In Proceedings of International Symposium on Communication Systems, Networks and DSPs, Staffordshire University, UK, 164--168.Google Scholar
Index Terms
- An intelligent agent with affect sensing from metaphorical language and speech
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