Advertisement

Artificial Intelligence Review

, Volume 16, Issue 2, pp 119–135 | Cite as

Current Directions in Computational Humour

  • Graeme Ritchie
Article

Abstract

Humour is a valid subject for research in artificial intelligence, as it is one of the more complex of human behaviours. Although philosophers and others have discussed humour for centuries, it is only very recently that computational work has begun in this field, so the state of the art is still rather basic. Much of the research has concentrated on humour expressed verbally, and there has been some emphasis on models based on “incongruity”. Actual implementations have involved puns of very limited forms. It is not clear that computerised jokes could enhance user interfaces in the near future, but there is a role for computer modelling in testing symbolic accounts of the structure of humorous texts. A major problem is the need for a humour-processing program to have knowledge of the world, and reasoning abilities.

affective computing artificial intelligence humour jokes puns 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Attardo, S. (1994). Linguistic Theories of Humour. Berlin: Mouton de Gruyter.Google Scholar
  2. Attardo, S. (1997). The Semantic Foundations of Cognitive Theories of Humor. HUMOR 4(10): 395-420.Google Scholar
  3. Attardo, S. & Raskin, V. (1991). Script Theory Revis(it)ed: Joke Similarity and Joke Representation Model. HUMOR 4(3): 293-347.Google Scholar
  4. Bates, J. (1994). The Role of Emotion in Believable Agents. Technical Report CMU-CS-94-136, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA.Google Scholar
  5. Binsted, K. (1995). Using Humour to Make Natural Language Interfaces more Friendly. In H. Kitano (ed.) Proceedings of the IJCAI Workshop on AI and Entertainment.Google Scholar
  6. Binsted, K., Pain, H. & Ritchie, G. (1997). Children's Evaluation of Computer-generated Punning Riddles. Pragmatics and Cognition 5(2): 309-358.Google Scholar
  7. Binsted, K. & Ritchie, G. (1994). An Implemented Model of Punning Riddles. In Proceedings of the Twelfth National Conference on Artificial Intelligence (AAAI-94). Seattle, USA.Google Scholar
  8. Binsted, K. & Ritchie, G. (1996). Speculations on Story Puns. In (Hulstijn and Nijholt, 1996), 151-159.Google Scholar
  9. Binsted, K. & Ritchie, G. (1997). Computational Rules for Generating Punning Riddles. HUMOR 10(1): 25-76.Google Scholar
  10. Chapman, A. J. & Foot, H. C. (eds.) (1976). Humour and Laughter: Theory, Research and Applications. London: Transaction Publishers, first edition.Google Scholar
  11. Curcó, C. (1996). Relevance Theory and Humorous Interpretations. In (Hulstijn and Nijholt, 1996), 53-68.Google Scholar
  12. Davies, C. (1990). Ethnic Humour around the World. Bloomington, Indiana.: Indiana University Press.Google Scholar
  13. Deckers, L. & Avery, P. (1994). Altered Joke Endings and a Joke Structure Schema. HUMOR 7(4): 313-321.Google Scholar
  14. Derks, P., Gillikin, L. S., Bartolome-Rull, D. S. & Bogart, E. H. (1997). Laughter and Electroencephalographic Activity. HUMOR 10(3): 285-300.Google Scholar
  15. Ephratt, M. (1990). What's in a Joke. In M. Golumbic (ed.) Advances in AI: Natural Language and Knowledge Based Systems. Springer Verlag, 43-74.Google Scholar
  16. Ephratt, M. (1996). More on Humor Act: What sort of Speech Act is the Joke? In (Hulstijn and Nijholt, 1996), 189-197.Google Scholar
  17. Fave, L. L., Haddad, J. & Maesen, W. A. (1976). Superiority, Enhanced Self-Esteem, and Perceived Incongruity Humour Theory. In (Chapman and Foot, 1976), Chapt. 4, 63-91.Google Scholar
  18. Freud, S. (1966). Jokes and Their Relation to the Unconscious. London: Routledge & Kegan Paul. First published 1905.Google Scholar
  19. Friedman, J. (1971). A Mathematical Model of Transformational Grammar. New York: American Elsevier.Google Scholar
  20. Friedman, J. (1972). Mathematical and Computational Models of Transformational Grammar. In B. Meltzer and D. Michie (eds.) Machine Intelligence 7. Edinburgh: Edinburgh University Press, 293-306.Google Scholar
  21. Frijda, N. H. & Moffat, D. (1993). A Model of Emotions and Emotion Communication. In Proceedings of RO-MAN 93: 2nd IEEE International Workshop on Robot and Human Communication, 29-34.Google Scholar
  22. Frijda, N. H. & Moffat, D. (1994). Modelling Emotion. Cognitive Studies 1(2): 5-15.Google Scholar
  23. Fry, W. F. (1994). The Biology of Humor. HUMOR 7(2): 111-126.Google Scholar
  24. Giles, H., Bourhis, R. Y., Gadfield, N. J., Davies, G. J. & Davies, A. P. (1976). Cognitive Aspects of Humour in Social Interaction: A Model and Some Linguistic Data. In (Chapman and Foot, 1976), Chapt. 7, 139-154.Google Scholar
  25. Godkewitsch, M. (1976). Physiological and Verbal Indices of Arousal in Rated Humour. In (Chapman and Foot, 1976), Chapt. 6, 117-138.Google Scholar
  26. Gruner, C. (1997). The Game of Humor. New Brunswick, NJ: Transaction Publishers.Google Scholar
  27. Hetzron, R. (1991). On the Structure of Punchlines. HUMOR 4(1): 61-108.Google Scholar
  28. Hobbs, J. (1990). Literature and Cognition, No. 21 in Lecture Notes. Stanford, California: Centre for the Study of Language and Information.Google Scholar
  29. Hulstijn, J. & Nijholt, A. (eds.) (1996). Proceedings of the InternationalWorkshop on Computational Humor, No. 12 in Twente Workshops on Language Technology. Enschede, Netherlands: University of Twente.Google Scholar
  30. Katz, B. (1993). A Neural Resolution of the Incongruity and Incongruity-Resolution Theories of Humour. Connection Science 5: 59-75.Google Scholar
  31. Katz, B. (1996). A Neural Invariant of Humour. In (Hulstijn and Nijholt, 1996), 103-109.Google Scholar
  32. Kitagaki, I. (1990). A Fuzzy Determination Method of Generating a Laugh and Popularity/Inferiority: “Students' Holiday” and “the Lowest in Running”. Journal of Japan Society for Fuzzy Theory and Systems 2(1): 100-104. In Japanese.Google Scholar
  33. Kitagaki, I. (1993). Extraction of Identity on Pronounciation Concerning Play-on-word and Evaluation of a Tentative Software: Aiming a Wordprocessor of Human Friendliness. Technical Report HC92-65, Institute of Electronics, Information and Communication Engineers of Japan. In Japanese.Google Scholar
  34. Koestler, A. (1970). The Act of Creation. London: Pan Books. First published 1964, Hutchinson & Co.Google Scholar
  35. Loehr, D. (1996). An Integration of a Pun Generator with a Natural Language Robot. In (Hulstijn and Nijholt, 1996), 161-172.Google Scholar
  36. McKay, J. (2000). Generation of Idiom-Based Witticisms to aid Second Language Learning. Master's thesis, Division of Informatics, University of Edinburgh, Edinburgh, Scotland.Google Scholar
  37. Miller, G. A., Beckwith, R., Fellbaum, C., Gross, D., Miller, K. & Tengi, R. (1990). Five Papers on WordNet. International Journal of Lexicography 3(4). Revised March 1993.Google Scholar
  38. Minsky, M. (1975). A Framework for Representing Knowledge. In P. H. Winston (ed.) The Psychology of Computer Vision. New York: McGraw-Hill, 211-277.Google Scholar
  39. Minsky, M. (1980). Jokes and the Logic of the Cognitive Unconscious. AI Memo 603, Massachusetts Institute of Technology, Artificial Intelligence Laboratory, Cambridge, Mass.Google Scholar
  40. Minsky, M. (1986). The Society of Mind. London: Heinemann.Google Scholar
  41. Norrick, N. R. (1993). Repetition in Canned Jokes and Spontaneous Conversational Joking. HUMOR 6(4): 385-402.Google Scholar
  42. Oaks, D. D. (1994). Creating Structural Ambiguities in Humor: Getting English Grammar to Cooperate. HUMOR 7(4): 377-401.Google Scholar
  43. Raskin, V. (1985). Semantic Mechanisms of Humour. Dordrecht: Reidel.Google Scholar
  44. Raskin, V. (1996). Computer Implementation of the General Theory of Verbal Humor. In (Hulstijn and Nijholt, 1996), 9-20.Google Scholar
  45. Raskin, V. & Attardo, S. (1994). Non-Literalness and Non-Bona-Fide in Language: Approaches to Formal and Computational Treatments of Humor. Pragmatics and Cognition 2(1): 31-69.Google Scholar
  46. Ritchie, G. (1999). Developing the Incongruity-Resolution Theory. In Proceedings of the AISB Symposium on Creative Language: Stories and Humour. Edinburgh, Scotland, 78-85.Google Scholar
  47. Ruch, W. (ed.) (1996). Special Issue: Measurement Approaches to Sense of Humor. HUMOR 9(3/4).Google Scholar
  48. Ruch, W., Attardo, S. & Raskin, V. (1993). Toward an Empirical Verification of the General Theory of Verbal Humour. HUMOR 6(2): 123-136.Google Scholar
  49. Schank, R. & Abelson, R. (1977). Scripts, Plans, Goals and Understanding. Hillsdale, NJ: Lawrence Erlbaum.Google Scholar
  50. Sperber, D. & Wilson, D. (1986). Relevance: Communication and Cognition. Oxford: Blackwell.Google Scholar
  51. Stock, O. (1996). Password Swordfish: Verbal Humour in the Interface. In (Hulstijn and Nijholt, 1996), 1-8.Google Scholar
  52. Takizawa, O., M. Y. amd Akira Ito & Isahara, H. (1996). On Computational Processing of Rhetorical Expressions-Puns, Ironies and Tautologies. In (Hulstijn and Nijholt, 1996), 39-52.Google Scholar
  53. Utsumi, A. (1996). Implicit Display Theory of Verbal Irony: Towards a Computational Model of Irony. In (Hulstijn and Nijholt, 1996), 29-38.Google Scholar
  54. Veale, T. & Keane, M. (1996). Bad Vibes: Catastrophes of Goal Activation in the Appreciation of Disparagement Humour and General Poor Taste. In (Hulstijn and Nijholt, 1996), 133-150.Google Scholar
  55. Zillmann, D. & Cantor, J. R. (1976). A Disposition Theory of Humour andMirth. In (Chapman and Foot, 1976), Chapt. 5, 93-115.Google Scholar

Copyright information

© Kluwer Academic Publishers 2001

Authors and Affiliations

  • Graeme Ritchie
    • 1
  1. 1.Division of InformaticsUniversity of EdinburghEdinburghScotland EH1 1HN

Personalised recommendations