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Inferring Pragmatics from Dialogue Contexts in Simulated Virtual Agent Games

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Agents for Educational Games and Simulations (AEGS 2011)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7471))

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Abstract

Virtual agents in video games may conduct two types of interactions: physical and dialogical. While the former is recognized as gazes and gestures, which received significant attention, the latter is often simplified in simulated virtual agent games. However, dialogical interactions affect the mental states of individual agents, and the relations between them, therefore playing a more important role than physical interactions in games. An implemented dynamic Bayesian Network (DBN) based on speech acts is proposed to model the dialogical effects as dialogue contexts in different aspects, such as emotion states, social relations, and social roles. We adopt a scene in the famous movie Doubt that has 53 dialogue sentences as the test corpus and implement 21 types of speech acts in the experiments. The results indicate that, with our DBN model, agents have the ability of context awareness to infer indirect speech acts from given direct speech acts, and that this ability may assist agents to plan dialogues based on speech acts in future work.

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References

  1. Ballmer, T., Brennenstuhl, W.: Speech Act Classification. Springer, Heidelberg (1981)

    Book  Google Scholar 

  2. Bartneck, C.: Integrating the OCC model of emotions in embodied characters. In: Proceedings of the Workshop on Virtual Conversational Characters: Applications, Methods, and Research Challenges, Melbourne (2002)

    Google Scholar 

  3. Bentahar, J., Moulin, B., Chaib-draa, B.: A persuasion dialogue game based on commitments and arguments. In: Proc. of the International Workshop on Argumentation in Multi-Agent Systems (2004)

    Google Scholar 

  4. Conati, C.: Probabilistic Assessment of User’s Emotions in Educational Games. Applied Artificial Intelligence 16(7-8), 555–575 (2002)

    Article  Google Scholar 

  5. Cozman, F.G.: Axiomatizing Noisy-OR. In: 16th European Conference on Artificial Intelligence, pp. 979–980. IOS Press, Valencia (2004)

    Google Scholar 

  6. Abowd, G.D., Dey, A.K., Brown, P.J., Davies, N., Smith, M., Steggles, P.: Towards a Better Understanding of Context and Context-Awareness. In: Gellersen, H.-W. (ed.) HUC 1999. LNCS, vol. 1707, pp. 304–307. Springer, Heidelberg (1999)

    Chapter  Google Scholar 

  7. Finin, T., Fritzson, R., McKay, D., McEntire, R.: KQML as an agent communication language. In: Proceedings of the Third International Conference on Information and Knowledge Management, pp. 456–463. ACM, Gaithersburg (1994)

    Google Scholar 

  8. Foundation for Intelligent Physical Agents (FIPA). FIPA Communicative Act Library Specification. FIPA00037, http://www.fipa.org/specs/fipa00037/

  9. Galley, M., Mckeown, K., Hirschberg, J., Shriberg, E.: Identifying agreement and disagreement in conversational speech: use of Bayesian network to model pragmatic dependencies. Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics, Stroudsburg, article 669, PA, USA (2004)

    Google Scholar 

  10. Grice, P.: Studies in the Way of Words, pp. 22–40. Harvard University Press (1989)

    Google Scholar 

  11. Inanoglu, Z., Caneel, R.: Emotive alert: HMM-Based emotion detection in voicemail messages. In: Proceedings of the 10th International Conference on Intelligent User Interfaces, pp. 251–253. ACM, San Diego (2005)

    Chapter  Google Scholar 

  12. Kim, S., Georgiou, P.G., Sungbok, L., Narayanan, S.: Real-time emotion detection system using speech: multi-model fusion of different timescale features. In: Proceedings of IEEE 9th Workshop Multimedia Signal Processing (MMSP), Chania, Greece, pp. 48–51 (2007)

    Google Scholar 

  13. Murphy, K.P.: Dynamic Bayesian Networks: Representation, Inference and Learning. Ph.D. Thesis, UC Berkley, USA (July 2002)

    Google Scholar 

  14. Poesio, M., Traum, D.: Representing conversation acts in unified Semantic/Pragmatic Framework. In: Proceedings of the AAAI Fall Symposium on Communicative Action in Humans and Machines (1997)

    Google Scholar 

  15. Pulman, S.G.: Conversation al games, belief revision and Bayesian networks. In: Proceedings of the 7th Computational Linguistics in the Netherlands Meeting (1996)

    Google Scholar 

  16. Russell, S., Norvig, P.: Artificial Intelligence: A Modern Approach, 3rd edn., pp. 566–599. Prentice Hall (2009)

    Google Scholar 

  17. Schilit, B.N., Adams, N., Want, R.: Context-aware computing applications. In: Proceedings of the Workshop on Mobile Computing System and Applications (1994)

    Google Scholar 

  18. Stolcke, A., Ries, K., Coccaro, N., et al.: Dialogue act modeling for automatic tagging and recognition of conversational speech. Computational Linguistics 26(3), 339–373 (2000)

    Article  Google Scholar 

  19. The script of the movie: Doubt, http://www.screenplaydb.com/film/scripts/doubt/

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Chien, A.YH., Soo, VW. (2012). Inferring Pragmatics from Dialogue Contexts in Simulated Virtual Agent Games. In: Beer, M., Brom, C., Dignum, F., Soo, VW. (eds) Agents for Educational Games and Simulations. AEGS 2011. Lecture Notes in Computer Science(), vol 7471. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32326-3_8

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  • DOI: https://doi.org/10.1007/978-3-642-32326-3_8

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-32325-6

  • Online ISBN: 978-3-642-32326-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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