COMPUTATIONAL HUMOURSeminar Presentation

Rohan, Avijit, Praveen, Ashutosh, Hemendra

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

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Outline

Problem Definition Structure of Common Verbal Jokes Theories of Humour Process of Automatic Humour Generation HAHAcronym system Conclusion

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Hemendra

Structure of Common Verbal Jokes1

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.

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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

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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

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Praveen

Theories of Humour2

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)

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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.

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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

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Rohan

General Theory of Verbal Humour3

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 opposition2. 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

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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. Target5. 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

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Demo

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

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Avijit

Humour Interpretation and Generation4

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

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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

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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

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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)

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Modifying the acronym expansion in a humorous way

HAHAcronym5

Humorous Ironic Acronym Re-analyzer

Resources used WordNet & WordNet Domains

Synsets tagged with Domain information Parser, morphological analyzer, etc

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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

root

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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

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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

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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

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Thank You for your patience !

Questions ?

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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, 2007

http://aath.org http://www.dcs.gla.ac.uk/~kimb/dai_version/subsection3_9_1.html

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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

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