The Impact of Semantic and Morphosyntactic Ambiguity on Automatic Humour Recognition

  • Antonio Reyes
  • Davide Buscaldi
  • Paolo Rosso
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5723)

Abstract

Humour is one of the most amazing characteristics that defines us as human beings and social entities. Its study supposes a deep insight into several areas such as linguistics, psychology or philosophy. From the Natural Language Processing (NLP) perspective, recent researches have shown that humour can be automatically generated and recognized with some success. In this work we present a study carried out on a collection of English texts in order to investigate whether or not semantic and morphosyntactic ambiguities may be employed as features in the automatic humour recognition task. The results we have obtained show that it is possible to discriminate humorous from non humorous sentences through features like perplexity or sense dispersion.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Attardo, S.: Linguistic Theories of Humor. Mouton de Gruyter, Berlin (1994)Google Scholar
  2. Attardo, S.: Humorous Texts: A semantic and pragmatic analysis. Mouton De Gruyter, Berlin (2001)Google Scholar
  3. Basili, R., Zanzotto, F.: Parsing Engineering and Empirical Robustness. Journal of Natural Language Engineering 8(3), 97–120 (2002)CrossRefGoogle Scholar
  4. Binsted, K.: Machine humour: An implemented model of puns. PhD thesis. University of Edinburgh, Edinburgh, Scotland (1996)Google Scholar
  5. Binsted, K., Ritchie, G.: Computational rules for punning riddles. Humor. Walter de Gruyter Co. 10, 25–75 (1997)CrossRefGoogle Scholar
  6. Binsted, K., Ritchie, G.: Towards a model of story puns. Humor 14(3), 275–292 (2001)CrossRefGoogle Scholar
  7. Buscaldi, D., Rosso, P.: Some experiments in Humour Recognition using the Italian Wikiquote collection. In: Masulli, F., Mitra, S., Pasi, G. (eds.) WILF 2007. LNCS (LNAI), vol. 4578, pp. 464–468. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  8. Jurafsky, D., Martin, J.: Speech and Language Processing: An introduction to natural language processing, computational linguistics, and speech recognition, Draft of June 25 (2007)Google Scholar
  9. Langacker, R.: Concept, Image and Symbol. In: The Cognitive Basis of Grammar. Mounton de Gruyter, Berlin (1991)Google Scholar
  10. Mihalcea, R.: Multidisciplinary Facets of Research on Humour. In: Masulli, F., Mitra, S., Pasi, G. (eds.) WILF 2007. LNCS (LNAI), vol. 4578, pp. 412–421. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  11. Mihalcea, R., Strapparava, C.: Technologies that make you smile: Adding humour to text-based applications. IEEE Intelligent Systems 21(5), 33–39 (2006)CrossRefGoogle Scholar
  12. Mihalcea, R., Strapparava, C.: Learning to Laugh (Automatically): Computational Models for Humor Recognition. Journal of Computational Intelligence 22(2), 126–142 (2006)CrossRefMathSciNetGoogle Scholar
  13. Mihalcea, R., Pulman, S.: Characterizing Humour: An Exploration of Features in Humorous Texts. In: Gelbukh, A. (ed.) CICLing 2007. LNCS, vol. 4394, pp. 337–347. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  14. Miller, G.: Wordnet: A lexical database. Communications of the ACM 38(11), 39–41 (1995)CrossRefGoogle Scholar
  15. Quasthoff, U., Richter, M., Biemann, C.: Corpus Portal for Search in Monolingual Corpora. In: Proceedings of the fifth international conference on Language Resources and Evaluation, LREC, pp. 1799–1802 (2006)Google Scholar
  16. Raskin, V.: Semantic Mechanisms of Humor. D. Reidel, Dordrecht (1985)Google Scholar
  17. Ruch, W.: The Perception of Humor. In: Kaszniak, A. (ed.) Emotion, Qualia, and Consciousness, Tokyo, pp. 410–425 (2001)Google Scholar
  18. Schmid, H.: Improvements in Part-of-Speech Tagging with an Application to German. In: Proceedings of the ACL SIGDAT Workshop (1995)Google Scholar
  19. Sjöbergh, J., Araki, K.: Recognizing Humor without Recognizing Meaning. In: Masulli, F., Mitra, S., Pasi, G. (eds.) WILF 2007. LNCS (LNAI), vol. 4578, pp. 469–476. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  20. Stock, O., Strapparava, C.: Hahacronym: A computational humor system. In: Demo Proc. of the 43rd annual meeting of the Association of Computational Linguistics (ACL 2005), pp. 113–116 (2005)Google Scholar
  21. Stolcke, A.: SRILM - An Extensible Language Modeling Toolkit. In: Proc. Intl. Conf. Spoken Language Processing, Denver, Colorado (2002)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Antonio Reyes
    • 1
  • Davide Buscaldi
    • 1
  • Paolo Rosso
    • 1
  1. 1.Natural Language Engineering Lab - ELiRF, Departa mento de Sistemas Informáticos y ComputaciónUniversidad Politécnica de ValenciaSpain

Personalised recommendations