Computational humor is a branch ofcomputational linguistics andartificial intelligence which usescomputers inhumor research. It is a relatively new area, with the first dedicated conference organized in 1996.[1]
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 computerpun generation were reported in the early 1990s,[2] based on anatural language generator program,VINCI.Graeme Ritchie andKim Binsted in their 1994 research paper described a computer program, JAPE, designed to generate question-answer-typepuns from a general, i.e., non-humorous, lexicon.[3] (The program name is an acronym for "Joke Analysis and Production Engine".) Some examples produced by JAPE are:
Since then the approach has been improved, and the latest report, dated 2007, describes the STANDUP joke generator, implemented in theJava programming language.[4][5] 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 ofcerebral palsy. (The project name is an acronym for "System To Augment Non-speakers' Dialog Using Puns" and an allusion tostandup comedy.) Children responded to this "language playground" with enthusiasm, and showed marked improvement on certain types of language tests.[4][6][7]
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 funnyacronyms.[8]
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).[9] There is an open-source Python implementation of Kiddon & Brun's TWSS system.[10]
A program to recognizeknock-knock jokes was reported by Taylor and Mazlack.[11] This kind of research is important in analysis of human–computer interaction.[12]
An application ofmachine learning techniques for the distinguishing of joke texts from non-jokes was described by Mihalcea and Strapparava (2006).[13]
Takizawaet al. (1996) reported on aheuristic program for detecting puns in theJapanese language.[14]
A possible application for assistance inlanguage 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] 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 inhuman–computer interaction is being investigated. In particular, humor generation inuser interface to ease communications with computers was suggested.[15][16][17]
Craig McDonough implemented the Mnemonic Sentence Generator, which convertspasswords into humorous sentences. Based on theincongruity 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 joinedQuayle's Ant, whileTARAR Jeopardizedthurmond's vase," an example chosen by combining politicians names with verbs and common nouns.[18]
John Allen Paulos is known for his interest in mathematical foundations of humor.[19] His bookMathematics 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 oncatastrophe 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.[20]
{{cite journal}}:Cite journal requires|journal= (help). Research Paper 688 University of Edinburgh, Edinburgh, Scotland, 1994, reported at the International Conference on Humor and Laughter, Luxembourg, 1993