Computational humor

An approach to analysis of humor is classification of jokes. A further step is an attempt to generate jokes basing on the rules that underlie classification.

Simple prototypes for computer pun generation were reported in the early 1990s,Lessard, G. and Levison, M. (1992). Computational modeling of linguistic humour: Tom Swifties. In ALLC/ACH Joint Annual Conference, Oxford, pages 175–178. based on a natural language generator program, VINCI. Graeme Ritchie and Kim Binsted in their 1994 research paper described a computer program, JAPE, designed to generate question-answer-type puns from a general, i.e., non-humorous, lexicon.{{cite journal |arxiv=cmp-lg/9406021 |last1=Binsted |first1=Kim |last2=Ritchie |first2=Graeme |title=A symbolic description of punning riddles and its computer implementation |year=1994 |bibcode=1994cmp.lg....6021B }}. Research Paper 688 University of Edinburgh, Edinburgh, Scotland, 1994, reported at the International Conference on Humor and Laughter, Luxembourg, 1993

• (conference proceeding version of the above) An implemented model of punning riddles. In Proceedings of the Twelfth National Conference on Artificial Intelligence (AAAI-94), Seattle, USA. (The program name is an acronym for "Joke Analysis and Production Engine".) Some examples produced by JAPE are:

:Q: What is the difference between leaves and a car?

:A: One you brush and rake, the other you rush and brake.

:Q: What do you call a strange market?

:A: A bizarre bazaar.

Since then the approach has been improved, and the latest report, dated 2007, describes the STANDUP joke generator, implemented in the Java programming language.Graeme Ritchie, Ruli Manurung, Helen Pain, Annalu Waller, Rolf Black, Dave O'Mara. "[http://homepages.abdn.ac.uk/g.ritchie/pages/papers/ijwcc07.pdf A practical application of computational humour]." In Cardoso, A. & Wiggins, G. (Ed.) Proceedings of the 4th. International Joint Workshop on Computational Creativity, London, UK, 2007, pp. 91–98.[https://www.abdn.ac.uk/ncs/departments/computing-science/standup-315.php STANDUP home page], with a link to free software download The STANDUP generator was tested on children within the framework of analyzing its usability for language skills development for children with communication disabilities, e.g., because of cerebral palsy. (The project name is an acronym for "System To Augment Non-speakers' Dialog Using Puns" and an allusion to standup comedy.) Children responded to this "language playground" with enthusiasm, and showed marked improvement on certain types of language tests.[http://www.csd.abdn.ac.uk/research/standup/cuttings/20060819_www.thecourier.co.uk.html "Laughter is the best therapy"] {{webarchive |url=https://web.archive.org/web/20070610153820/http://www.csd.abdn.ac.uk/research/standup/cuttings/20060819_www.thecourier.co.uk.html |date=June 10, 2007 }}, The Courier, 19 August 2006[http://news.bbc.co.uk/1/hi/scotland/5276366.stm "Joke software helps non-speakers"], BBC News, 22 August 2006

The two young people, who used the system over a ten-week period, regaled their peers, staff, family and neighbors with jokes such as: "What do you call a spicy missile? A hot shot!" Their joy and enthusiasm at entertaining others was inspirational.

Stock and Strapparava described a program to generate funny acronyms.Stock, Oliviero and Strapparava, Carlo

• (2003) "HAHAcronym: Humorous agents for humorous acronyms." Humor: International Journal of Humor Research, 16(3):297–314.
• (2005). "The act of creating humorous acronyms." Applied Artificial Intelligence, 19(2):137–151.
• (2006) [http://www.aaai.org/Papers/AAAI/2006/AAAI06-278.pdf Laughing with HAHAcronym, a Computational Humor System], Proceedings of the AAAI Conference on Artificial Intelligence, 21, pp. 1675-1678

A statistical machine learning algorithm to detect whether a sentence contained a "That's what she said" double entendre was developed by Kiddon and Brun (2011).Chloe Kiddon and Yuriy Brun (2011). "[http://www.aclweb.org/anthology/P/P11/P11-2016.pdf That's What She Said: Double Entendre Identification."] In Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies, pages 89–94, Portland, Oregon,

USA, June. Association for Computational Linguistics. There is an open-source Python implementation of Kiddon & Brun's TWSS system.[https://github.com/tansaku/twss GitHub – tansaku/twss: A Python project inspired by the research of Chloé Kiddon and Yuriy Brun. Part of the Funniest Computer Ever Open Source initiative]

A program to recognize knock-knock jokes was reported by Taylor and Mazlack.Taylor, J. M. and Mazlack, L. J. (2004). "Computationally recognizing wordplay in jokes". In Proceedings of Cognitive Science Conference, pages 2166–2171, Stresa, Italy. This kind of research is important in analysis of human–computer interaction.[http://www.uc.edu/News/NR.aspx?ID=6139 "UC Researchers Design Humorous 'Bot'"] {{webarchive |url=https://web.archive.org/web/20100602033631/http://www.uc.edu/News/NR.aspx?ID=6139 |date=June 2, 2010 }}

An application of machine learning techniques for the distinguishing of joke texts from non-jokes was described by Mihalcea and Strapparava (2006).Mihalcea, R. and Strapparava, C. (2006). "Learning to laugh (automatically): Computational models

for humor recognition." Computational Intelligence, 22(2):126–142.

Takizawa et al. (1996) reported on a heuristic program for detecting puns in the Japanese language.Osamu Takizawa, Masuzo Yanagida, Akira Ito, and Hitoshi Isahara (1996). "On Computational Processing of Rhetorical Expressions – Puns, Ironies and Tautologies". In (Hulstijn and Nijholt, 1996), 39–52.

A possible application for assistance in language acquisition is described in the section "Pun generation". Another envisioned use of joke generators is in cases of a steady supply of jokes where quantity is more important than quality. Another obvious, yet remote, direction is automated joke appreciation.

It is known {{citation needed|date=April 2015}} that humans interact with computers in ways similar to interacting with other humans that may be described in terms of personality, politeness, flattery, and in-group favoritism. Therefore, the role of humor in human–computer interaction is being investigated. In particular, humor generation in user interface to ease communications with computers was suggested.Rada Mihalcea, Carlo Strapparava, "Technologies That Make You Smile: Adding Humor to Text-Based Applications", IEEE Intelligent Systems, 2006, vol. 21, no.5, pp. 33–39. DOI: http://doi.ieeecomputersociety.org/10.1109/MIS.2006.104Graeme Ritchie (2001) "[http://citeseer.ist.psu.edu/cache/papers/cs/21251/http:zSzzSzwww.dai.ed.ac.ukzSzhomeszSzgraemezSzpaperszSzcurrent_directions.pdf/graeme01current.pdf Current Directions in Computer Humor]", Artificial Intelligence Review. 16(2): pages 119–135[http://wwwhome.cs.utwente.nl/~anijholt/artikelen/ctit24_2002.pdf M.P. Mulder, A. Nijholt, (2002) "Humour Research: State of the Art"]

Craig McDonough implemented the Mnemonic Sentence Generator, which converts passwords into humorous sentences. Based on the incongruity theory of humor, it is suggested that the resulting meaningless but funny sentences are easier to remember. For example, the password AjQA3Jtv is converted into "Arafat joined Quayle's Ant, while TARAR Jeopardized thurmond's vase," an example chosen by combining politicians names with verbs and common nouns.Craigh McDonough (2001) "Using Natural Language Processing for random Passwords", Technical Report, CERIAS, Purdue University (unpublished), as quoted by Mulder and Nijholt (2002)

John Allen Paulos is known for his interest in mathematical foundations of humor.John Allen Paulos (1980, 1982) "Mathematics and Humor: A Study of the Logic of Humor", 1982 paperback: {{ISBN|0-226-65025-1}}, Japanese translation, 1983, Dutch translation, 1990 His book Mathematics and Humor: A Study of the Logic of Humor demonstrates structures common to humor and formal sciences (mathematics, linguistics) and develops a mathematical model of jokes based on catastrophe theory.

Conversational systems which have been designed to take part in Turing test competitions generally have the ability to learn humorous anecdotes and jokes. Because many people regard humor as something particular to humans, its appearance in conversation can be quite useful in convincing a human interrogator that a hidden entity, which could be a machine or a human, is in fact a human.Shah, H. and Warwick, K., "Machine Humour: Examples from Turing Test Experiments", AI & Society, Vol.32, pp553-561, 2017.

• Theory of humor
• World's funniest joke#Other findings

• "[https://web.archive.org/web/20110926220406/http://www.computer.org/portal/cms_docs_intelligent/intelligent/homepage/590206.pdf Computational humor]", by Binsted, K.; Nijholt, A.; Stock, O.; Strapparava, C.; Ritchie, G.; Manurung, R.; Pain, H.; Waller, A.; Oapos;Mara, D., IEEE Intelligent Systems Volume 21, Issue 2, 2006, pp. 59 – 69 {{doi|10.1109/MIS.2006.22}}
• O. Stock, C. Strapparava & A. Nijholt (eds.) "The April Fools' Day Workshop on Computational Humour." Proc. Twente Workshop on Language Technology 20 (TWLT20), ISSN 0929-0672, ITC-IRST, Trento, Italy, April 2002, 146 pp

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Category:Artificial intelligence

Category:Computational linguistics

Category:Humor research

Category:Computational fields of study