Abstract
In this paper, we propose a system which produces funny proverbs. This system uses the punch line framework named Sukashi. That is, by changing the end of the line, the proposed system produces a funny sentence. In this system, we employ Google N-grams to make a lot of Sukashi candidates. After that, the system extracts parameters from each word in each candidate. We choose parameters such as words’ sounding, length, imageability, similarity and concrete level. The system selects candidates by using fuzzy rules. The performance of the proposed system has been evaluated by subjective experiments and obtained satisfactory results.
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References
De Boni, M., Richardson, A., Hurling, R.: Humour, Relationship Maintenance and Personality Matching in Automated Dialogue: A Controlled Study. Interact. Comput. 20(2), 342–353 (2007)
Binsted, K., Takizawa, O.: BOKE – A Japanese Punning Riddle Generator. Journal of the Japanese Society for Artificial Intelligence 13(6), 920–927 (1997)
Waller, A., Black, R., O’Mara, D.A., Pain, H., Ritchie, G., Manurung, R.: Evaluating the STANDUP Pun Generating Software with Children with Cerebral Palsy. ACM Trans. Access. Comput. 1(3), 1–27 (2009)
Fukui, N.: The Techniques for Making Laugher – Laugh Makes Us Discover the World, Sekai Shisousya (2002)
Yet Another Part-of-Speech and Morphological Analyzer, http://mecab.sourceforge.net/
Kudo, T., Kazawa, H.: Japanese Google N-grams, vol.1. Gengo-Shigen-Kyokai (GSK)
Oda, S.: Laughing and Humor. Chikuma Shobo (1986)
Needleman, S.B., Wunsch, C.D.: A General Method Applicable to the Search for Similarities in the Amino Acid Sequence of Two Proteins. Journal of Molecular Biology 48(3), 443–453 (1970)
Sabsevitz, D., Medler, D., Seidenberg, M., Binder, J.: Modulation of the Semantic System by Word Imageability. Neuro Image 27(1), 188–200 (2005)
Sakuma, N., Ijuin, M., Fushimi, T., Tatsumi, I., Tanaka, M., Amano, S., Kondo, K.: “NTT Database Series ”Japanese Vocabulary Attribution. Word Imageability 8(1) (2005)
Ishikawa Laboratory, Takushoku University, Computational System for the Similarity between Concepts(Words), http://www.cs.takushoku-u.ac.jp/ai/ruiji/Similarity_System.cgi
Noguchi, Y., Shimizu, R., Sugimoto, K., Ishikawa, T.: An Improved Tool for Measuring Semantic Similarity between Words. In: The 69th National Convention of Information Processing Society of Japan, vol. 2, pp. 2545–2546 (March 2007)
Kawashima, T., Ishikawa, T.: An Evaluation of Knowledge Base of Words and Thesaurus on Measuring the Semantic Similarity between Words. In: The 18th Annual Conference of the Japanese Society for Artificial Intelligence, vol. 18, pp. 2D2–2D10 (2004)
Shoten, I.: Nihongo Goi-Taikei CD-ROM, http://www.kecl.ntt.co.jp/mtg/resources/GoiTaikei/
Sugeno, M.: Fuzzy Control. Nikkan Kogyo (1988)
Kurogo, T.: Kurogo’s Proverb Dictionary, http://www.geocities.jp/tomomi965/
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Yamane, H., Hagiwara, M. (2010). A Funny Proverb Generation System Based on Sukashi . In: Diamantaras, K., Duch, W., Iliadis, L.S. (eds) Artificial Neural Networks – ICANN 2010. ICANN 2010. Lecture Notes in Computer Science, vol 6354. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15825-4_49
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DOI: https://doi.org/10.1007/978-3-642-15825-4_49
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