Affect creativity-humor

Affect,Crea+vity,andHumor:Computa+onalChallenges

AlessandroValitu<UniversityCollegeDublin

InvitedTalkattheDepartmentofComputerScience,UniversityofBari“A.Moro”25May2016

AbstractThelastdecadehasseentheemergenceofnewresearchareascalled"affec+vecompu+ng","computa+onalcrea+vity",and"computa+onalhumor".Theautomatedrecogni+onofsen+mentsandopinionshasbecomeastabletrackofthetopAr+ficialIntelligenceconferences.Agrowingnumberofinterna+onalprojectsarefocusingontheimplementa+onofformsofcrea+vity.Morerecently,theideaofbuildingcomputerprogramscapableofrecognizingandgenera+nghumorisnotconsideredunachievableasinthepast.Inthistalk,Iwillgiveasummaryofmyexperienceinthesenewareasofcomputerscience.Morespecifically,Iamgoingtodescribesomeoftheideas,resources,andmethodsdevelopedduringmyresearchac+vity.

OutlineAffect:•  Affec+velexicalresources:WordNet-Affect•  LatentSeman+cAnalysisforaffectrecogni+on:Affec+veWeight•  Affec+vetextanima+onCrea+vity:•  Computa+onalCrea+vityareas•  Crea+veSystems•  DynamicalsystemsandbasinjumpingHumor:Computa+onalhumorgenera+onHumorousvaria+onoffamiliarexpressionsLexicalreplacementhumor

WordNet-Affect•  WordNetisanon-linelexicalreferencesystemwhosedesignisinspiredbypsycholinguis,ctheoriesofhumanlexicalmemory

•  Englishnouns,verbs,adjec+vesandadverbsareorganizedintosynonymsets(synsets),eachrepresen+nganunderlyinglexicalconcept

•  InWordNet-Affectwehaveanaddi+onalhierarchyofaffec,vedomainlabels

A-LabelsandsomeexamplesA-Label Examples of Synsets

EMOTION noun "anger#1", verb "fear#1"

MOOD noun "animosity#1", adjective "amiable#1"

TRAIT noun "aggressiveness#1", adjective "competitive#1"

COGNITIVE STATE noun "confusion#2", adjective "dazed#2"

PHYSICAL STATE noun "illness#1", adjective "all_in#1"

HEDONIC SIGNAL noun "hurt#3", noun "suffering#4"

EMOTION-ELICITING SITUATION noun "awkwardness#3", adjective "out_of_danger#1"

EMOTIONAL RESPONSE noun "cold_sweat#1", verb "tremble#2"

BEHAVIOUR noun "offense#1", adjective "inhibited#1"

ATTITUDE noun "intolerance#1", noun "defensive#1"

SENSATION noun "coldness#1", verb "feel#3"

Freely available (for research purposes) athttp://wndomains.itc.it

Valencetagging

•  Dis+nguishingsynsetsaccordingtoemo+onalvalence

•  Posi,veemo+ons(joy#1,enthusiasm#1),•  Nega,veemo+ons(fear#1,horror#1),•  Ambiguous,whenthevalencedependsonthecontext(surprise#1),

•  Neutral,whenthesynsetisconsideredaffec+vebutnotcharacterizedbyvalence(indifference#1)

Affec+veHierarchy(Screenshots)

Affec+veWeight

1.  WordNet-Affectprovidestherepresenta+onofdirectaffec,vewords

2.  LatentSeman+cAnalysis(LSA)givesameasureofthesimilaritybetweendirectaffec+vetermsandindirectaffec,vewords

LSAspaced3

d1

d2

synset = w1+ w2 + w3

term = w1

§ Similarity: cosine among vectors

Anexample:universityRelated emotional terms Positive emotional category

university Enthusiasm

professor Sympathy

scholarship Devotion

achievement Encouragement

Related emotional terms Negative emotional category

university Downheartedness

professor Antipathy

study Isolation

scholarship Melancholy

Affec+veweightofnews+tles

•  Weanalyzedthewordscontainedineachsentence,andextractthewordwithhigheraffec+veweight

News titles (Google-news) Emotion Word with highest affective weight

Review: `King Kong’ a giant pleasure Joy pleasure#n

Romania: helicopter crash kills four people Fear crash#v

Record sales suffer steep decline Sadness suffer#v

Dead whale in Greenpeace protest Anger protest#v

Textanima+on(1)

•  Kine,ctypography:textsthatusemovementsorotherperceptualchangesover+me

•  Itaddsafurthercommunica+vedimensiontosimpletext

•  Wewanttoexploitalinkbetweenlexicalseman+csoftextsandsomekine+cproper+esforanima+ngthem

Textanima+on(2)

•  Weusedasastar+ngpointthekine,ctypographyengine[Leeetal.2002]

•  Webuiltadevelopmentenvironmentandascrip,nglanguagefordynamicalcrea+onoftextanima+ons

•  Composing(e.g.joining,addinginparallel,…)elementaryanima+onsasbuildingblocks

•  Elementaryanima+ons:linear,oscillate,pulse,jitter,etc.

Kine+cbehavior:e.g.“anger”

We annotated each emotion category in Wordnet-affect with an appropriate kinetic behavior

Emo+onalkine+cbehaviors

•  E.g.Imita+nghumanresponses

•  Joy:asequenceofhops•  Fear:palpita+ons•  Anger:strongtrembleandblush•  Surprise:suddenswellingoftext•  Sadness:textdefla+onandsquashing

Affec+veTextAnima+onü  Newsheadlines(takenformGoogle-News)

•  Twomainsteps:(i)emo+onrecogni+onand(ii)kine+canima+onassembling

1.  Recognizetheemo+onalcategoryoftheheadline2.  Markthewordsthatareclosertothatemo+on3.  Assigntheproperaffec+veanima+ontoeachword4.  Assembleacomprehensiveanima+onscript,anddisplaythe

animated+tle

IronyDefini+onTheterm"irony"canrefertodifferentconcepts:•  Situa+onalirony:situa+oncharacterizedbycontrastbetween

realityandhumanidealsorinten+ons(alsocalled"ironyofthefate").

•  Verbalirony:isarhetoricaldeviceinwhichtheintendedmeaningofstatementsisdifferentfrom(andtypicallyoppositeof)theliteralmeaning.Whatissaidisoppositeofwhatismeant.

•  Ifonelooksoutofhiswindowatarainstormandremarkstoafriend,"Gloriousday,isn'tit?"thecontradic+onbetweenthefactsandtheimplieddescrip+onisaformofverbalirony.

•  Seman+ccontrastcanbeemployedinbothtypesofirony.Wefocusonverbalirony.

•  Polarity-based(verbal)irony:Thepolarityofwhatissaidisoppositetothepolarityofwhatismeant.["glorious"->"miserable”]

Irony

ConceptualCrea+vity Linguis+cCrea+vity

Situa+onalIrony VerbalIrony

Polarityopposi+onasaseman+cdeviceforbothconceptualandlinguis+ccrea+vity

ResearchQues+ons

•  Towhatextentisitpossibletogenerateverbalironyautoma+cally?

•  Howcanweevaluateverbalironyofcomputer-generatedsentencesusingacrowdsourcingsystem?

•  Towhatdegreeseman+ccontrastusedinsitua+onalironyisalsocapabletoachieveverbalirony?

@MetaphorMagnet(1)•  ItisaTwioerbot@MetaphorMagnet,whichusesastoreofknowledgetocreatetweetsthataremeanttobemeaningful(Veale2014).

•  Thesystemcangeneratearichrangeofcrea+vestatements,whichareregularlypostedonTwioer.

Example:Rememberwhenpeacewasencouragedbynonviolentpeacemakers?Now,peaceisavictoryenjoyedonlybyconqueringvictors.

@MetaphorMagnet(2)

@MetaphorMagnet(3)Asubsetsofthetweetpaoernsaredesignedtobeinten+onallyironic.#Irony:Whensomesovereignslivein"magnificent"palacesthewayrappersliveinwretchedgheoos.#Sovereign=#Rapper#Palace=#Gheoo#Irony:Thinkersformula+ngpromisingideasaboutfu+lefantasy.#Promising=#Fu+le#IdeaAboutFantasy#Irony:Themostdignifiedstatesmanisnotmorecelebratedthanthemostunprofessionalblogger.#Statesman=#Blogger

IronyFactors,IronyMarkers,Echo

Therearethreemainbuildingblocks:1.  Seman+cContent:IronyFactors2.  Pragma+ccues:IronyMarkers3.  Background(i.e.contextual)knowledge:

EchoedInforma+on

#Irony:Thinkersformula+ngpromisingideasaboutfu+lefantasy.#Promising=#Fu+le#IdeaAboutFantasy



EchoedInforma+on

#Irony:Thinkersformula+ngpromisingideasaboutfu+lefantasy.



EchoedInforma+on




EchoedInforma+on




EchoedInforma+on

#Irony:Thinkersformula+ngpromisingideasaboutfu+lefantasy. (E.g.,arerapoli+calspeech)

Evalua+onofAutoma+c(Verbal)Irony•  Wecanuseaironygeneratorasatestbedforthegenera+onofrandomizedsamples.

•  Eachexperimentalse<ngcorrespondstodifferentcombina+onsoflinguis+cfeatures.

•  Therefore,wecanusethesystemtostudythecontribu+onofspecificlinguis+cfeaturestothepercep+onofirony.

•  Ontheotherhand,ifthelinguis+cfeaturescanbecontrolledbygenera+veparameters,theevalua+onisnotonlyabouttheironyoftextsbutalsoaboutthesystemcapabilitytogenerateironictexts.

•  Exampleoflinguis+cproper+esthatcannotbecontrolledbygenera+veparameters:sen+mentofthewholesentence.

ExperimentalSe<ngs

BASE Thevegetablesaremixedinhealthfulsalads.

QUOT Thevegetablesthataremixedin“healthful”salads.

HASH #Irony:Thevegetablesaremixedinhealthfulsalads.

QUOT+COMP Thevegetablesthataremixedin“healthful”saladsaretreatedwithpoisonouspes,cides.

QUOT+HASH #Irony:Thevegetablesthataremixedin“healthful”saladsaretreatedwithpoisonouspes,cides.

Computa+onalCrea+vityAreasResearchArea Crea+veSystem

crea+vitystudies:computa+onalmodellingofhumancrea+vity

humans

machinecrea+vity computerprogram:artefactsgenerator

computer-supportedcrea+vity

computer-program+user

Essen+alProper+es

(Ritchie2007,pp.72-73):

1.  Typicality:Howmuchtheartefactisanexampleofagivengenre

2.  Novelty:howmuchtheartefactisdissimilartoexis+ngexamplesofitsgenre

3.  Quality[=Value]

•  Typicalitycanbeusedtoevaluate“weakcrea+vity”•  Allthreeproper+escanbeusedtoevaluate“strong

crea+vity”

Creative Systems

(Wiggins2006):•  Theconceptualspaceisasetofartefacts(inBoden’sterms,concepts)whichareinsomequasi-syntac+csensedeemedtobeacceptableasexamplesofwhateverisbeingcreated.Implicitly,theconceptualspacemayincludepar+allydefinedartefactstoo.

•  Exploratorycrea-vityistheprocessofexploringagivenconceptualspace

39ICCBR-1528September2015

Creative Systems


(Ritchie2007):

•  setofbasicitemsB=datatypes(e.g.stringofwords,arraysofpixels)characterisingtheartefactsproducedbytheprogram

•  setofresultsR=setofartefactsproducedbytheprogramwithaspecificsetofse<ngparameters

•  inspiringsetI:Theconstruc+onoftheprogramisinfluenced(eitherexplicitlyorimplicitly)bysomesubsetoftheavailablebasicitems.Thissubset,whichwewillcalltheinspiringset,couldbealltherelevantartefactsknowntotheprogramdesigner,oritemswhichtheprogramisdesignedtoreplicate,oraknowledgebaseofknownexampleswhichdrivesthecomputa+onwithintheprogram.

Inspiringset(Ritchie2007,pp.76)

Defini+on:“Theinspiringsetisthesetincluding]alltherelevantartefactsknowntotheprogramdesigner,oritemswhichtheprogramisdesignedtoreplicate,oraknowledgebaseofknownexampleswhichdrivesthecomputa+onwithintheprogram.”

•  Whyisitusefultointroducetheinspiringset?Wecouldsaythataprogramismorecrea+veifdoesnotreplicate(orcloselyimitate)theinstanceswhichguideditsdesign.

B

Setofbasicitems

B

I

Inspiringset

B

I

Setofresults

R

B

IR

TypicalartefactsTα,1(R)={x∈R|α≤typ(X)≤1}

Tα,1(R)

B

IR

ValuableartefactsVγ,1(R)={x∈R|γ≤val(X)≤1}

Vγ,1(R)

B

IR

TypicalandvaluableartefactsVγ,1(R)∩Tα,1(R)

Vγ,1(R)∩Tα,1(R)

Crea+veSystemsasDynamicalSystems

•  Aconceptualspaceofacrea+vesystemcanbedecomposedinseveralregionscalled“basinsofaorac+ons”,eachassociatedtoaspecifictypeofartefacts.

•  Weproposetwoformsofsimilaritybetweenartefacts,accordingtotypicality(t-similarity)andvalue(v-similarity).


The Fractal Tree


28September2015 ICCBR-15 50

TheFractalTree























Paths and Attractors

Whatisapathinthe“squareoffractaltrees”?1.  Asearchintheconceptualspaceofacrea+vesystem2.  Atrajectoryinthephasespaceofadynamical

systemAnaQractorisasetofstates(i.e.,elementsofthestatespaceofadynamicalsystem)towardswhichasetofdynamicalpathstendtoevolve.Thesetofdynamicalpathspoin+ngtotheaoractoriscalledbasinofaQrac+on.


Basin Jumping and Creativity

•  Theconceptualspacecanbedecomposedinbasinsofaorac+on.•  Star+ngfromasetofpastexamples(inspira+onset),acrea+ve

systemcanreachfromwhichaspecificbasinofaorac+oncanbeexplored.

•  “ClassicCBR”allowsacrea+vesystemtoexplorethebasinofaorac+oncontainingthesetofpastexamples(assumedtobetheinspira+onset)

•  “Crea+veCBR”shouldallowsacrea+vesystemtoreachbasinofaorac+onsnotcontainingthepastexamples

•  Insummary,ifweassumethecrea+vityasasearchintheconceptualspace,ahigherdegreeofcrea+vityisassociatedtothesearchofnewbasinsofaorac+on(basinjumping).


Double Similarity

•  CBRisbasedonthecapabilitytorecognizeanewcaseassimilartooneofthepastcases

•  Crea+veCBRshouldemploytwoformsofsimilarity:–  T-Similarity:degreetowhichtwoartefactsarerecognisedasbelongingtothesametype

–  V-Similarity:degreetowhichthevalueoftwoartefactsisrecognisedassimilar

•  T-similarityallowsthesystemtoexplorethecurrentbasinofaorac+on

•  V-similarityallowsthesystemtoreachdifferentbasinsofaorac+on


Humour

•  Defini+on:Capabilitytointen+onallyinduce–  mirth–  laughter–  smile

•  Mirthinduc+onisperformedthroughlanguage

emotion

cognition

language

(VerbalInten+onal)Humor

HumorinComputers(2)

Computa+onalHumor

•  Itisaresearcharealyingattheintersec+onbetweenComputa+onalLinguis+csandAr+ficialIntelligence.

•  Itmainlyaimsattheimplementa+onoftoolsabletogenerateandrecognizehumorautoma+cally,butalsocancontributetothestudyofhumorthroughcomputa+onalmodels.

•  Prototypesdevelopedsofarareverylimited,ifcomparedtothehumancapabilitytounderstandandproducehumor.Inmostcases,theyareabletoproducespecifictypesofhumoroustexts(e.g.shortjokesorpunsbasedonwordplays).

Computa+onalHumorGenera+onExamplesofoutputsfromhumorgenerators:•  Ritchie,Binsted

o  linguis+canalysisofjokes[2004]o  punningriddle[BinstedandRitchie,1994]o  e.g.:“Whatdoyoucallamurdererwithfibre?Acerealkiller.”

•  Stock,Strapparavao  largescalelexicalresources,seman+crela+ons,crea+vevaria+onso  funnyhacronyms[2003]o  e.g.:“MIT=MythicalIns+tuteofTheology”

•  Nijholt,Tinholto  humorousagents:interac+on,appropriatedness,humorousactso  anaphoricalpuns[2004]o  e.g.:“MaryaskedSusanaques+on,andshegavetheanswer”“Did

Marygivetheanswer?”

FamiliarExpressionsVaria+on

•  Wordsubs+tu+ononfamiliarexpressions(e.g.,proverbs,movie+tles,etc.)

•  Twowordsgivenasinput:atopicword(e.g.‘holidays’,‘food’,etc.)andanemo+onword(e.g.‘joy’,‘fear’)

•  Searchofpossiblecandidatewordsforthesubs+tu+on(inalistofEnglishwords):o  wordphone+callysimilartosomewordinatleastone

familiarexpressiono  wordseman+callyrelatedtothetopicwordandthe

emo+onword

(Valitu<etal.2008):

Examples

(‘crash’,‘fear)SaturdayFrightFever

(‘surgery’,‘fear’)BacktotheSuture

(‘den+st’,‘fear’)FatalExtrac+on

(‘beach’,‘joy’)TomorrowisanotherBay

StepbyStepExample

surgery

BacktotheSuture

futuresuturejurassicthoracic

aorac+onextrac+on

symptomtherapy

metabolismanalgesicextrac+onthoracicsuture

futureJurassic

abstrac+onaorac+oncontrac+ondiffrac+ondistrac+oninac+onreac+onretrac+onsubtrac+ontransac+on

fear

MovieTitlesandTabooWords

JAPE:Genera+onofHumorousPunningRiddlesExamplebyGraemeRitchie(2004)

Choosetwowordsthatsoundsthesame

What do you call a ?

! A

(Anadjec+ve) (Anoun)

meansroughlythesameas




! A



bare bear

naked teddy

bare bear




! A



bizarre

bazaar

market strange

bizarre

bazaar


Humorgenera+onbylexicalreplacement

(Valitu<etal.2013)

•  ResearchQues+on:towhatextentacomputerprogramcantransformagenericshorttextasinputandmakeithumorouswithasinglewordsubs+tu+on?

•  Keyelements:

o  automatedgenera+onofhumorousexpressionsbylexicalreplacement.

o  AdultHumor

o  Useoftaboowordsasawaytointroducefunnyinappropriateness

ExamplesfromDamnYouAutocorrect.com

Correooreautoma+co

Humorgenera+onprocedureHumorgenera+onbylexicalreplacement:1.  TheproceduregetsasinputasegmentofEnglishtext

(e.g.:“Leteverythingturnwellinyourlife!”).2.  Thenitperformsasinglewordsubs+tu+on(e.g:‘life’

replacedwith‘wife’)andreturnstheresul+ngtext.3.  Tomakeitfunny,thewordsubs+tu+onisperformed

accordingtoanumberoflexicalconstraints:formconstraints,tabooconstraint,andcontextualconstraints.

4.  Addi+onally,thetextcanbeappendedwithaphrasesuchas“Imean‘life’not‘wife’}”.

FormalconstraintsTheoriginalwordanditssubs+tutearesimilarinform:•  Orthographicsimilarity:twowordsareconsidered

orthographicallysimilarifonewordisobtainedwithasinglecharacterdele+on,addi+on,orreplacementfromtheotherone

•  Phone+csimilarity:Wecalltwowordsphone+callysimilariftheirphone+ctranscrip+onisorthographicallysimilaraccordingtotheabovedefini+on

•  Rhyme:Twowordsrhymeiftheyhavesameposi+onsoftonicaccent,andiftheyarephone+callyiden+calfromthemoststressedsyllabletotheendoftheword

TabooconstraintsThesubs+tutewordisatabooword:

•  Taboowordsarewordsnormallyavoidedineverydayconversa+onsbecauseperceivedasinappropriate

•  Theycanrefertobodyproducts,bodyparts,sexualacts,ethnicorracialinsults,profanity,vulgarity,etc.

•  Wecollectedalistof700taboowordsasunionofthreesubsets:

o  Wordsmanuallyselectedfromanavailablelistofwordsreferringtotheseman+cdomain“sexuality”

o  Profani+esandslangterms

o  Wordsfromexamplesofhumorousautocorrect

ContextualconstraintsThesubs+tu+ontakesplaceattheendofthetext,andina

locallycoherentmanner•  Localcoherence=thesubs+tutewordformsafeasible

phrasewithitsimmediatepredecessor,inordertoexpandthetaboomeaningtothephraselevel

•  Theseman+ccontrastisassumedstrongerifthetaboowordcomesasasurpriseintheendofaseeminglyinnocenttext.

•  Localcoherenceisimplementedusingn-grams.Weusedthe2012GoogleBooksn-gramscollec+on

ExamplesofoutputsExperimentalcondi+on Output

FORM Ohoh...Denmuzchangeplatliao...Gobackhaveyanjiuagain...Not'plat'...'plan'.

FORM Josaskifuwanameltup?'meet'not'melt'!

FORM+TABOO Gotcaughtintherain.Waitedhalfnhourinthebussstop.Not'buss'...'bus'!

TABOO Heypple...$700or$900for5nights...Excellentmasturba+onwifbreakfasthamper!!!SorryImean'loca+on'

FORM+TABOO+CONT Nope...Juzofffromberk...SorryImean'work'

FORM+TABOO+CONT I'vesentyoumyfart...Imean'part'not'fart'...

ConclusiveKeywords•  NLrecogni+onvs.NLgenera+on•  Interdisciplinarity•  Lexicalresourcesandlexicalvectorspaces•  Conceptualspacesandexploratorycrea+vity•  Evalua+onofnoveltasksandhypothesistes+ng•  Focusonsubjec+veresponse•  Crea+vereuse•  Interac+vity•  Mul+modality

LexicalResources

LexicalVectorSpaces

ConceptualSpaces

SpacesofSubjec+veResponse

ReferencesAffec+veNLP:•  A.Valitu<,C.Strapparava,andO.Stock.“DevelopingAffec+veLexicalResources”.PublishedinPsychNology

Journal,ISSN1720-7525,2(1):61-83,2004.•  C.StrapparavaandA.Valitu<.“WordNet-Affect:anAffec+veExtensionofWordNet”.AcceptedattheFourth

Interna+onalConferenceonLanguageResourcesandEvalua+on(LREC2004).May26-28,Lisbon,2004.•  A.Valitu<andC.Strapparava.“InterfacingWordNet-AffectwithOCCmodelofemo+ons”.AcceptedattheThird

Interna+onalWorkshoponEMOTION2010-CorporaforresearchonEmo+onandAffect,pp.16-19,May23,2010,Valleoa,Malta.

•  A.Valitu<andT.Veale.InducinganIronicEffectinAutomatedTweets.Acceptedatthe6thInterna+onalConferenceonAffec+veCompu+ngandIntelligentInterac+on(ACII2015),Xi'an,China,pp.153-159,September21-24,2015.

Computa+onalCrea+vity:•  A.Valitu<,C.Strapparava,andO.Stock.“TextualAffectSensingforComputa+onalAdver+sing”.Acceptedatthe

AAAISpringSymposiumonCrea+veIntelligentSystems,March26-28,2008,StanfordUniversity,PaloAlto,California.

•  AlessandroValitu<.Crea+veSystemsasDynamicalSystems.AcceptedattheWorkshoponExperienceandCrea+vity(ICCBR-2015),pp.146-150,FrankfurtamMain,Germany,28September2015.

Computa+onalHumor:•  A.Valitu<.“HowManyJokesareReallyFunny?TowardsaNewApproachtotheEvalua+onofComputa+onal

HumourGenerators”.8thInterna+onalWorkshoponNaturalLanguageProcessingandCogni+veScience(NLPCS2011),2011..

•  A.Valitu<,H.Toivonen,A.Doucet,andJ.M.Toivanen."LetEverythingTurnWellinYourWife":Genera+onofAdultHumorUsingLexicalConstraints.ACL2013.

•  A.Valitu<,A.Doucet,J.M.Toivanen,andH.Toivonen(2015).Computa+onalGenera+onandDissec+onofLexicalReplacementHumor.NaturalLanguageEngineering.

•  AValitu<andT.Veale.InfusingHumorinUnexpectedEvents.HCIInterna+onal2016,Toronto.

Technology

Affect creativity-humor