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COMPUTATIONAL HUMOUR Seminar Presentation Rohan, Avijit, Praveen, Ashutosh, Hemendra
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Problem Definition Modeling verbal humour in a computationally tractable way Other kinds of humour Cartoons Given some keywords Create a humorous text from it Problem of recognizing humorous text is a different problem Ashutosh AgarwalSeminar Presentation 2
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Outline Problem Definition Structure of Common Verbal Jokes Theories of Humour Process of Automatic Humour Generation HAHAcronym system Conclusion Ashutosh AgarwalSeminar Presentation 3
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Hemendra Structure of Common Verbal Jokes 1
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One liners Short sentence with comic effects Simple syntax, deliberate use of rhetoric devices Frequent use of creative language constructions Humor-producing features are guaranteed to be present in the first (and only) sentence. Suitable for use in an automatic learning setting. Eg. Take my advice; I don’t use it anyway. Beauty is in the eye of the beer holder. HemendraSeminar Presentation 5
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Punning Riddles Question-answer riddle Uses phonological ambiguity. Question and Answer in single sentence Eg. What do shortsighted ghosts wear? Spooktacles How do you make gold soup? Put 24 carrots in it HemendraSeminar Presentation 6
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Wordplay Jokes Depend on words that are similar in sound Used in two different meanings Difference between the two meanings creates a conflict breaks expectation Clifford: The Postmaster General will be making the TOAST. Woody: Wow, imagine a person like that helping out in the kitchen! I shot a elephant in my pajamas. I will always wonder how he got in there. HemendraSeminar Presentation 7
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Praveen Theories of Humour 2
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Superiority Theory We laugh about the misfortunes of others It reflects our own superiority With such jokes, we are laughing AT someone, not laughing WITH them Every situation has a winner and a loser The winner is the one that successfully makes fun of the loser There’s something about Mary (1998) Deewane Huye Pagal (2005) PraveenSeminar Presentation 9
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Relief Theory Laughter releases tension & psychic energy Psychic energy builds up as an aid for suppressing feelings in taboo areas, like sex or death. When psychic energy is released we experience laughter because release of psychic energy Because taboo thoughts are being entertained Pleasant sensation experienced when humor replaces negative feelings like pain or sadness. PraveenSeminar Presentation 10
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Incongruity Theory Incongruity Dictionary meaning: “Disagreement of parts” A joke has two parts : setup & punchline Setup has 2 meanings One meaning is most obvious, other meaning remains hidden Punch line suddenly brings the less obvious meaning in spotlight This disagreement of setup and punch line is called incongruity PraveenSeminar Presentation 11
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Rohan General Theory of Verbal Humour 3
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General Theory of Verbal Humour (GTVH) “How many Poles does it take to screw in a light bulb? Five. One to hold the bulb and four to turn the table he's standing on.” 1. Script opposition 2. Logical mechanism – figure-ground reversal “How many Poles does it take to screw in a light bulb? Five. One to hold the light bulb and four to look for the right screwdriver” – false analogy RohanSeminar Presentation 13
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GTVH – contd. 3. Situation “How many Poles does it take to wash a car? Two. One to hold the sponge and one to move the car back and forth.” 4. Target 5. Narrative strategy “It takes five Poles to screw in a light bulb: one to hold the light bulb and four to turn the table he's standing on.” – expository text 6. Language RohanSeminar Presentation 14
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Demo
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“You know what’s weird? Donald duck never wore pants… But, whenever he’s getting out of the shower, he always puts a towel around his waist… I mean, what is that about?” - Chandler Script opposition – dumb vs. non-dumb Logical mechanism – inconsistency Situation – shower scene of Donald duck Target – Disney cartoon character ‘Donald duck’ Narrative strategy – irony Language – 2 sentences – 2 oppositions RohanSeminar Presentation 17
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Avijit Humour Interpretation and Generation 4
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Surprise Disambiguation for Jokes Based on the incongruity resolution theory Joke consists of a set-up and a punchline Two interpretations of set-up one more obvious than the other Punchline creates incongruity Cognitive rule has to be found out for punchline to follow the set-up naturally AvijitSeminar Presentation 19
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Surprise Disambiguation for Jokes Some essential properties One Obvious interpretation of set-up Conflict of punchline with obvious set-up Compatibility of punchline with hidden set-up Comparison between two set-ups Inappropriateness of hidden set-up Another approach : Violation of prediction of set- up AvijitSeminar Presentation 20
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Model for Punning Riddles Syllable substitution What do shortsighted ghost’s wear? Spooktacles Word Substitution How do you make gold soup? Put 24 carrots in it Metathesis What is the difference between an oak tree and a tight shoe? One makes acorns, the other makes corns ache AvijitSeminar Presentation 21
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Word Substitution List of homophones already available Lexicon consists of lexemes and lexical relations Two requirements: schema and template Schema : Relations between lexemes Template: Information to turn schema and lexemes into piece of text Eg. JAPE (Joke Analysis and Production Engine) AvijitSeminar Presentation 22
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Modifying the acronym expansion in a humorous way HAHAcronym 5
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Humorous Ironic Acronym Re-analyzer Resources used WordNet & WordNet Domains Synsets tagged with Domain information Parser, morphological analyzer, etc MIT – Massachusetts Institute of Technology Mythical Institute of Technology ACM-Association of computing machinery Association for confusing machinery AshutoshSeminar Presentation 24
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WordNet Domains 250 domain labels Hierarchy of domains Opposing semantic fields On the basis of study of jokes Examples Religion Vs Technology Sex Vs Religion Religion Theology Mythology Art Photography Music Theatre Philosophy Logic Semantics root AshutoshSeminar Presentation 25
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Abstract Architecture Parse the acronym Choice of what to keep unchanged What to keep unchanged Typically it is the head of the NP Search for possible substitutions Using semantic field oppositions WordNet antonymy relations AshutoshSeminar Presentation 26
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Evaluation Human evaluation Students from universities 70% acronyms were found to be funny System won Jury’s special prize in a laughter challenge AshutoshSeminar Presentation 27
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Conclusion In this presentation Humour theories Humour Generation techniques Example humour generating system Humour research is useful for Designing better human computer interaction systems Computer aided joke generation Rohan, Praveen, Avijit, Ashutosh & HemendraSeminar Presentation 28
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Thank You for your patience ! Questions ? 29
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References F.R.I.E.N.D.S. … M. Mulder and A. Nijholt, Humour Research : State of the Art, University of Twente, Center for Telematics and Information Technology, Technical Report CTIT- 02-34, Septeber 2002, 24 pp. Stock, O. and Strapparava, C. 2005. HAHAcronym: a computational humor system. In Proceedings of the ACL 2005 on interactive Poster and Demonstration Sessions (Ann Arbor, Michigan, June 25 - 30, 2005). Annual Meeting of the ACL. Association for Computational Linguistics, Morristown, NJ, 113-116. DOI= http://dx.doi.org/10.3115/1225753.1225782. Characterizing Humour: An Exploration of Features in Humorous Texts, Lecture Notes in Computer Science, Springer Berlin / Heidelberg, ISSN: 0302-9743 (Print) 1611-3349 (Online), Volume 4394/2007, Saturday, May 19, 2007Lecture Notes in Computer Science http://aath.org http://aath.org http://www.dcs.gla.ac.uk/~kimb/dai_version/subsection3_9_1.html http://www.dcs.gla.ac.uk/~kimb/dai_version/subsection3_9_1.html 30
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Demo “You know what’s weird? Donald duck never wore pants… But, whenever he’s getting out of the shower, he always puts a towel around his waist… I mean, what is that about?” - Chandler Script opposition – dumb vs. non-dumb Logical mechanism – inconsistency Situation – shower scene of Donald duck Target – Disney cartoon character ‘Donald duck’ Narrative strategy – irony Language – 2 sentences – 2 oppositions RohanSeminar Presentation 31
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