Why did the computer cross the road?

Linguists are trying to get computers to do very human things: detect humour, recognise irony, and even write jokes. But can computers do funny? What makes something funny, anyway?

Linguist Daniel Midgley hacks the humour mainframe on this episode of Talk the Talk.


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199: Computer Humour

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Promo

Promo with Em Burrows, 2015-04-07: Compuhumour

Show notes

Gina Williams in the Guardian: “Gina Williams on why every Australian should know some Indigenous words”
http://www.theguardian.com/music/2015/mar/28/gina-williams-on-why-every-australian-should-know-some-indigenous-words

Discovering the land and its people through Noongar place names
http://www.abc.net.au/local/stories/2015/04/01/4209443.htm

Boodjar: Nyungar Placenames in the South-West of Western Australia
http://www.boodjar.org.au/

Department of Education: Contrary to popular belief, the ‘up’ at the end of south west town names does not reflect ‘plenty of water’ but ‘place of”.
http://www.det.wa.edu.au/aboriginaleducation/apac/detcms/aboriginal-education/apac/regions/southwest/aboriginal-place-names.en?cat-id=9192406

Australian Kids Are Learning the Warumungu Language With a Radio Cockatoo’s Help
http://globalvoicesonline.org/2015/04/03/australian-kids-are-learning-the-warumungu-language-with-radio-cockatoos-help/

“Pinarra Aku”
http://barklyarts.com.au/pinarra-aku-2/

Ethnologue: Warumungu
http://www.ethnologue.com/language/wrm

What is comedy and what makes something funny?
http://www.thinctanc.co.uk/words/comedy.html

Scientists Discovered What Makes Something Funny
http://www.businessinsider.com.au/bob-mankoff-science-of-funny-humor-new-yorker-cartoon-2014-12

Fawlty Towers: The Hotel Inspectors
http://www.dailymotion.com/video/x27poly_fawlty-towers-s01e04-the-hotel-inspectors_shortfilms

Abbott and Costello: Who’s on First?

Norm MacDonald’s moth joke
http://www.break.com/video/the-moth-joke-norm-macdonald-2519827

Norm Macdonald and the moth joke: Analysis
http://www.metafilter.com/147672/Regarding-Norm-Macdonald-and-the-moth-joke

Huge list of humour in NLP
http://meta-guide.com/dialog-systems/natural-language-generation/joke-generators/

Zhang and Liu: Recognizing Humor on Twitter
http://dl.acm.org/citation.cfm?id=2661997

Taylor and Mazlack: Computationally Recognizing Wordplay in Jokes
http://www.ece.uc.edu/~mazlack/academic.UC/Taylor.CogSci04.pdf

The Science Behind “That’s What She Said” (TWSS)
http://www.extremetech.com/extreme/84244-the-science-behind-thats-what-she-said-twss

[Subject] Could Eat [Object] All Day. That’s What She Said.
http://www.slate.com/blogs/browbeat/2011/05/03/subject_could_eat_object_all_day_that_s_what_she_said.html

Kiddon and Brun: “That’s What She Said: Double Entendre Identification”
http://www.aclweb.org/anthology/P11-2016

Ong, et al: Automatically Extracting Templates from Examples for NLP Tasks

http://anthology.aclweb.org//Y/Y08/Y08-1048.pdf

Evaluating the STANDUP Pun Generating Software with Children with Cerebral Palsy.
http://www.researchgate.net/publication/220535519_Evaluating_the_STANDUP_Pun_Generating_Software_with_Children_with_Cerebral_Palsy

The STANDUP project
http://inf.abdn.ac.uk/research/standup/

All Things Linguistic: Nope
http://allthingslinguistic.com/post/115516629596/nope-tildes-and-twitter-dialects

“Nope” intensifies, diversifies grammatically
https://stancarey.wordpress.com/2014/12/22/nope-intensifies-diversifies-grammatically/

House full of Nopespiders, apparently filmed in Nopesico City.

Nope.

NOPE.

The Word Detective: Nope
http://www.word-detective.com/2009/09/nope/

Language Log: Yep and Nope
http://languagelog.ldc.upenn.edu/nll/?p=2768

Online Etymology Dictionary: nope
http://www.etymonline.com/index.php?term=nope

Was this poem written by a bot, or not?
http://botpoet.com/


Image credit:
http://www.quickmeme.com/img/e7/e722ba857ec1af4ef3060e8a550421c99394144c62e09385da4e30d892600d56.jpg