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Towards Joking, Humor Sense Equipped and Emotion Aware Conversational Systems

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Advances in Affective and Pleasurable Design

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 483))

Abstract

In this paper, we present our progress so far in realization of project aimed to create a complex, modular humor-equipped conversational system. By complex, we mean that it should be able to: (1) detect users’ emotions, (2) detect users’ humorous behaviors and react to them properly, (3) generate humor according to users’ emotive states and (4) learn each user’s individual sense of humor. The research is conducted in Japanese. We chose puns as a relatively computable genre of humor. We describe a general outline of our system, as well as its four modules: humor detection module, emotion recognition module, response generator module and individualisation module. We present the algorithm of systems used in each module, along with some evaluation results.

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References

  1. Yokogawa, T.: Japanese Pun analyzer using articulation similarities. In: Proceedings of the FUZZ-IEEE’02, pp. 1114–1119. Hawaii, USA (2002)

    Google Scholar 

  2. Amaya, Y., Rzepka, R., Araki, K.: Performance evaluation of recognition method of narrative humor using words similarity. In: SIG-LSE-B303, pp. 63–69 (2013) (in Japanese)

    Google Scholar 

  3. Kitagaki, I.: A case study of development of a “comnuter that can laugh” based on an induction model of laughableness. J. Japan Soc. Fuzzy Theory Intell. Inf. 15(5), 577–583 (2003) (in Japanese)

    Google Scholar 

  4. Grefenstette, G., Qu, Y., Shanahan, J.G., Evans, D.A.: Coupling niche browsers and affect analysis for an opinion mining. In: Proceedings of RIAO-04, pp. 186–194. Avignon, France (2004)

    Google Scholar 

  5. Elliott, C.: The affective reasoner: a process model of emotions in a multi-agent system. Unpublished doctoral dissertation, Northwestern University Institute for the Learning Sciences, Chicago, USA (1992)

    Google Scholar 

  6. Liu, H., Lieberman, H., Selker, T.: A model of textual affect sensing using real-world knowledge. In: Proceedings of IUI 2003, pp. 125–132. Florida, USA (2003)

    Google Scholar 

  7. Alm, C.O., Roth, D., Sproat, R.: Emotions from text: machine learning for text based emotion prediction. In: Proceedings of HLT/EMNLP, pp. 579–586. Vancouver, Canada (2005)

    Google Scholar 

  8. Aman, S., Szpakowicz, S.: Identifying expressions of emotion in text. In: Proceedings of TSD-2007, LNCS 4629, pp. 196–205. Springer, Berlin/Heidelberg (2007)

    Google Scholar 

  9. Tsuchiya, S., Yoshimura, E., Watabe, H., Kawaoka, T.: The method of the emotion judgment based on an association mechanism. J. Nat. Lang. Process. 14(3), 219–238 (2007)

    Article  Google Scholar 

  10. Shi, W., Rzepka, R., Araki, K.: Emotive information discovery from user textual input using causal associations from the internet. In: Proceedings of FIT2008, pp. 267–268. Japan (2008) (in Japanese)

    Google Scholar 

  11. Tokuhisa, R., Inui, K., Matsumoto, Y.: Emotion classification using massive examples extracted from the web. In: Proceedings of Coling 2008, pp. 881–888. Manchester, UK (2008)

    Google Scholar 

  12. Ptaszynski, M., Dybala, P., Shi, W., Rzepka, R., Araki, K.: A system for affect analysis of utterances in Japanese supported with web mining. J. Japan Soc. Fuzzy Theory Intell. Inf. 21(2), 30–49 (2009)

    Google Scholar 

  13. Binsted, K.: Machine humour: an implemented model of puns. Ph.D. Dissertation, University of Edinburgh, UK (1996)

    Google Scholar 

  14. Ritchie, G., Manurung, R., Pain, H., Waller, A., Black, R., O’Mara, D.: A practical application of computational humour. In: Cardoso, A., Wiggins, G.A. (eds.) Proceedings of the 4th International Joint Conference on Computational Creativity, pp. 91–98. UK, London (2007)

    Google Scholar 

  15. Tinholt, H.W., Nijholt, A.: Computational humour: utilizing cross-reference ambiguity for conversational jokes. In: Proceedings of WILF 2007. Camogli, Italy. LNAI, vol. 4578, pp. 477–483. Springer, Berlin (2007)

    Google Scholar 

  16. Sjobergh, J., Araki, K.: A very modular humor enabled Chat-Bot for Japanese. In: Proceedings of PACLING 2009, pp. 135–140. Hokkaido University, Sapporo, Japan (2009)

    Google Scholar 

  17. Dybala, P., Ptaszynski, M., Rzepka, R., Araki, K.: Extending the chain: humor and emotions in human computer interaction. Int. J. Comput. Linguist. Res. 1(3), 116–125 (2010)

    Google Scholar 

  18. Cortes, C., Vapnik, V.: Support-vector networks. Mach. Learn. 20(3), 273–297 (1995)

    MATH  Google Scholar 

  19. Ptaszynski, M., Masui, F., Dybala, P., Rzepka, R., Araki, K.: Open source affect analysis system with extensions. In: Proceedings of iHAI 2013, Sapporo, Japan (2013)

    Google Scholar 

  20. Ptaszynski, M., Dybala, P., Rzepka, R., Araki, K.: Affecting corpora: experiments with automatic affect annotation system—a case study of the 2channel forum. In Proceedings of PACLING-09, pp. 223–228. Hokkaido University, Sapporo, Japan (2009)

    Google Scholar 

  21. Russell, J.A.: A circumplex model of affect. J. Pers. Social Psychol. 39(6), 1161–1178 (1980)

    Article  Google Scholar 

  22. Ptaszynski, M., Maciejewski, J., Dybala, P., Rzepka, R., Araki, K.: CAO: a fully automatic emoticon analysis system based on theory of kinesics. IEEE Trans. Affect. Comput. 1(1), 46–59 (2010)

    Article  Google Scholar 

  23. Higuchi, S., Rzepka, R., Araki, K.: A casual conversation system using modality and word associations retrieved from the web. In: Proceedings of the Conference on Empirical Methods in Natural Language Processing. Association for Computational Linguistics (2008)

    Google Scholar 

  24. Dybala, P.: Humor to Facilitate HCI. Lambert Academic Publishing, Germany (2011)

    Google Scholar 

  25. Dybala, P., Ptaszynski, M., Maciejewski, J., Takahashi, M., Rzepka, R., Araki, K.: Multiagent system for joke generation: humor and emotions combined in human-agent conversation. J. Ambient Intell. Smart Environ. (Thematic Issue on Computational Modeling of Human-Oriented Knowledge within Ambient Intelligence) 2(2010), 31–48 (2010)

    Google Scholar 

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Correspondence to Pawel Dybala .

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Dybala, P., Yatsu, M., Ptaszynski, M., Rzepka, R., Araki, K. (2017). Towards Joking, Humor Sense Equipped and Emotion Aware Conversational Systems. In: Chung, W., Shin, C. (eds) Advances in Affective and Pleasurable Design . Advances in Intelligent Systems and Computing, vol 483. Springer, Cham. https://doi.org/10.1007/978-3-319-41661-8_64

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  • DOI: https://doi.org/10.1007/978-3-319-41661-8_64

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