Alan Smaill – författare

The research fields of "artificial intelligence and music" and "cognitive musicology" are relative newcomers to the many interdisciplinary groupings based around the centre of AI and cognitive science. They are concerned with the computational study and emulation of human behaviour with respect to music, in many aspects, and with varying degrees of emphasis on psychological plausibility. Recent publications have included work in such diverse areas as rhythm and pitch perception, performance, composition, and formal analysis. Music shares with language the property of giving access to human mental behaviour in a very direct way. As such, it has the potential to be a very useful domain for AI work. Furthermore, in the course of time, AI related work will surely throw light back onto some or all of the fields to which it is applied. Indeed, we are already beginning to feel the benefits of the application of AI techniques to music technology. It is not surprising, therefore, that one of the first areas interest for of musical AI study is that of music education. There are many ways in which an artificial intelligence or cognitive science approach to music education may be applied - for example, to automate tuition, to explain learning processes, to provide metaphors for human computer interaction, and so on. This collection of papers, which is intended to give an impression of both the breadth and depth of the field, originated from a workshop entitled "Music Education: An Artificial Intelligence Approach".

The research fields of "artificial intelligence and music" and "cognitive musicology" are relative newcomers to the many interdisciplinary groupings based around the centre of AI and cognitive science. They are concerned with the computational study and emulation of human behaviour with respect to music, in many aspects, and with varying degrees of emphasis on psychological plausibility. Recent publications have included work in such diverse areas as rhythm and pitch perception, performance, composition, and formal analysis. Music shares with language the property of giving access to human mental behaviour in a very direct way. As such, it has the potential to be a very useful domain for AI work. Furthermore, in the course of time, AI related work will surely throw light back onto some or all of the fields to which it is applied. Indeed, we are already beginning to feel the benefits of the application of AI techniques to music technology. It is not surprising, therefore, that one of the first areas interest for of musical AI study is that of music education. There are many ways in which an artificial intelligence or cognitive science approach to music education may be applied - for example, to automate tuition, to explain learning processes, to provide metaphors for human computer interaction, and so on. This collection of papers, which is intended to give an impression of both the breadth and depth of the field, originated from a workshop entitled "Music Education: An Artificial Intelligence Approach".

Thisvolumecontainsthefullresearchpapersofthe2nd International Con- renceonMusicandArti?cialIntelligence(ICMAI02),heldinSt. Cecilia'sHall, Edinburgh,UK,12-14September2002. Theconferencewasjointlyorganizedby theFacultyofMusicandtheDivisionofInformatics,UniversityofEdinburgh. Eachofthepapersinthisvolumewasrefereedbyatleastthreereviewersfrom theProgramCommittee. AdditionalpaperswereacceptedasWork-in-Progress reports,publishedseparatelybytheDivisionofInformaticsoftheUniversity ofEdinburgh. Theconferenceprogramalsoincludedround-tablediscussions, electronicmusicconcerts,earlykeyboardintrumentdemonstrations,andvarious socialevents. Thefocusoftheconferencewasontheinterplaybetweenmusicaltheoryand practiceontheonehandandtechniquesandmethodsfromArti?cialIntelligence, includingcomputationalcognitivemodelingofmusicalprocesses,ontheother. Weareespeciallyinterestedinissuesofmusicalrepresentationandanalysis, associatedalgorithms,andtheevaluationofmusicalartefacts. MusicpresentsmanychallengesforAIandInformaticsingeneral. Whilethe analogieswithnaturallanguageandwithvisionareproductive,musicrequires novelsolutionstoitsownrepresentationalandalgorithmicproblems.Forthe musician,workinthisareacontributestowardsmusicologicalstudy,composition, performance,interactivesystems,andsoundsynthesis. Threedistinguishedscholarsinthearea,MiraBalaban,Jean-ClaudeRisset, andAntonioCamurri,agreedtogivetheinvitedkeynotes. Thesetalkscovered di?erentfeaturesofmusicalexperienceanditsrelationtoArti?cialIntelligence, namelymusicalconcepts,composition,andperformance. Morespeci?cally,Jean- ClaudeRisset'stopicwasMusicalCompositionandArti?cialIntelligence:Some Precedents and Prospects,MiraBalaban'swas Structure and Interpretation of Music Concepts - Music from a Computational Perspective,andAntonio- murri'swasComputationalModelsofExpressiveGesture. Thepapersintheconferencedealtwithawiderangeofaspectsofcurrent research,includingstructural,harmonic,andreductionalmusicanalysis,pattern representationanddiscoveryinbothmonophonicandpolyphonicmusic,music perceptionofmelodyandrhythm,therelationbetweenmusicandnaturallan- age,similarityandcategorization,musicandintonation,musicalexpressionand performance,soundprocessing,soundclassi?cations,commercialapplications, andmusicontheweb. Acknowledgements.Theeditorsaregratefulforallthehelpofthosewho madethepublicationofthisvolumepossible,andespeciallyDarrellConklin, VI Organization PeterNelson,EmiliosCambouropoulos,AlisonPease,andMarkSteedman;also, JordanFleming,EwenMaclean,andRobertDow;andtheFacultyofMusicand theDivisionofInformatics,UniversityofEdinburghfor?nancialsupport. July2002 ChristinaAnagnostopoulou MiguelFerrand AlanSmaill OrganizingCommittee AlanSmaill(Chair) ChristinaAnagnostopoulou(Co-chair) MiguelFerrand PeterNelson AlisonPease MarkSteedman ProgramCommittee ?JensArnspang(Alborg) GillianHayes(Edinburgh) MiraBalaban(Ben-Gurion) HenkjanHoning(Nijmegen) MartaOlivettiBelardinelli(Rome) JukkaLouhivuori(Jyvaskyla) RensBod(Amsterdam) TodMachover(MIT-MediaLab) CarolaBoehm(Glasgow) GuerinoMazzola(ZurichandVienna) AmilcarCardoso(Coimbra) StephenMcAdams(IRCAM) EmiliosCambouropoulos(Thessaloniki)EduardoMiranda(SONYCSL-Paris) ElaineChew(USC) PeterNelson(Edinburgh) DarrellConklin(ZymoGenetics) Fran,coisPachet(SONYCSL-Paris) IanCross(Cambridge) StephenTravisPope(SantaBarbara) RogerDannenberg(CMU) AlanSmaill(Edinburgh) PeterDesain(Nijmegen) MarkSteedman(Edinburgh) AnastasiaGeorgaki(Athens) DavidTemperley(Rochester) InvitedSpeakers MiraBalaban(Ben-GurionUniversity,Israel) AntonioCamurri(UniversityofGenoa,Italy) Jean-ClaudeRisset(LaboratoiredeM'echaniqueetd'14September2002. Theconferencewasjointlyorganizedby theFacultyofMusicandtheDivisionofInformatics,UniversityofEdinburgh. Eachofthepapersinthisvolumewasrefereedbyatleastthreereviewersfrom theProgramCommittee. AdditionalpaperswereacceptedasWork-in-Progress reports,publishedseparatelybytheDivisionofInformaticsoftheUniversity ofEdinburgh.Theconferenceprogramalsoincludedround-tablediscussions, electronicmusicconcerts,earlykeyboardintrumentdemonstrations,andvarious socialevents. Thefocusoftheconferencewasontheinterplaybetweenmusicaltheoryand practiceontheonehandandtechniquesandmethodsfromArti?cialIntelligence, includingcomputationalcognitivemodelingofmusicalprocesses,ontheother. Weareespeciallyinterestedinissuesofmusicalrepresentationandanalysis, associatedalgorithms,andtheevaluationofmusicalartefacts. MusicpresentsmanychallengesforAIandInformaticsingeneral. Whilethe analogieswithnaturallanguageandwithvisionareproductive,musicrequires novelsolutionstoitsownrepresentationalandalgorithmicproblems. Forthe musician,workinthisareacontributestowardsmusicologicalstudy,composition, performance,interactivesystems,andsoundsynthesis. Threedistinguishedscholarsinthearea,MiraBalaban,Jean-ClaudeRisset, andAntonioCamurri,agreedtogivetheinvitedkeynotes. Thesetalkscovered di?erentfeaturesofmusicalexperienceanditsrelationtoArti?cialIntelligence, namelymusicalconcepts,composition,andperformance. Morespeci?cally,Jean- ClaudeRisset'stopicwasMusicalCompositionandArti?cialIntelligence:Some Precedents and Prospects,MiraBalaban'swas Structure and Interpretation of Music Concepts - Music from a Computational Perspective,andAntonio- murri'swasComputationalModelsofExpressiveGesture.Thepapersintheconferencedealtwithawiderangeofaspectsofcurrent research,includingstructural,harmonic,andreductionalmusicanalysis,pattern representationanddiscoveryinbothmonophonicandpolyphonicmusic,music perceptionofmelodyandrhythm,therelationbetweenmusicandnaturallan- age,similarityandcategorization,musicandintonation,musicalexpressionand performance,soundprocessing,soundclassi?cations,commercialapplications, andmusicontheweb. Acknowledgements. Theeditorsaregratefulforallthehelpofthosewho madethepublicationofthisvolumepossible,andespeciallyDarrellConklin, VI Organization PeterNelson,EmiliosCambouropoulos,AlisonPease,andMarkSteedman;also, JordanFleming,EwenMaclean,andRobertDow;andtheFacultyofMusicand theDivisionofInformatics,UniversityofEdinburghfor?nancialsupport. July2002 ChristinaAnagnostopoulou MiguelFerrand AlanSmaill OrganizingCommittee AlanSmaill(Chair) ChristinaAnagnostopoulou(Co-chair) MiguelFerrand PeterNelson AlisonPease MarkSteedman ProgramCommittee ?JensArnspang(Alborg) GillianHayes(Edinburgh) MiraBalaban(Ben-Gurion) HenkjanHoning(Nijmegen) MartaOlivettiBelardinelli(Rome) JukkaLouhivuori(Jyvaskyla) RensBod(Amsterdam) TodMachover(MIT-MediaLab) CarolaBoehm(Glasgow) GuerinoMazzola(ZurichandVienna) AmilcarCardoso(Coimbra) StephenMcAdams(IRCAM) EmiliosCambouropoulos(Thessaloniki)EduardoMiranda(SONYCSL-Paris) ElaineChew(USC) PeterNelson(Edinburgh) DarrellConklin(ZymoGenetics) FranccoisPachet(SONYCSL-Paris) IanCross(Cambridge) StephenTravisPope(SantaBarbara) RogerDannenberg(CMU) AlanSmaill(Edinburgh) PeterDesain(Nijmegen) MarkSteedman(Edinburgh) AnastasiaGeorgaki(Athens) DavidTemperley(Rochester) InvitedSpeakers MiraBalaban(Ben-GurionUniversity,Israel) AntonioCamurri(UniversityofGenoa,Italy) Jean-ClaudeRisset(LaboratoiredeM'echaniqueetd'Acoustique,France) TableofContents InvitedTalks StructureandInterpretationofMusicConcepts:Musicfroma ComputationalPerspective...1 MiraBalaban ExpressiveGesture...4 AntonioCamurri RegularContributions AGeneralParsingModelforMusicandLanguage ...5 RensBod TheSpiralArray:AnAlgorithmforDeterminingKeyBoundaries ...18 ElaineChew RepresentationandDiscoveryofVerticalPatternsinMusic ...32 DarrellConklin DiscoveringMusicalStructureinAudioRecordings...43 RogerB. Dannenberg,NingHu RealTimeTrackingandVisualisationofMusicalExpression ...58 SimonDixon,WernerGoebl,GerhardWidmer AutomaticClassi?cationofDrumSounds:AComparisonofFeature SelectionMethodsandClassi?cationTechniques...69 PerfectoHerrera,AlexandreYeterian,FabienGouyon SomeFormalProblemswithSchenkerianRepresentationsofTonal Structure ...81 TimHorton RespirationRe?ectingMusicalExpression:AnalysisofRespiration duringMusicalPerformancebyInductiveLogicProgramming ...94 SohIgarashi,TomonobuOzaki,KoichiFurukawa MimeticDevelopmentofIntonation ...107 EduardoReckMiranda InteractingwithaMusicalLearningSystem:TheContinuator ...119 Fran,coisPachet VIII TableofContents RecognitionofIsolatedMusicalPatternsUsingHiddenMarkovModels ...133 AggelosPikrakis,SergiosTheodoridis,DimitrisKamarotos AModelforthePerceptionofTonalMelodies...144 Dirk-JanPovel ControlLanguageforHarmonisationProcess ...155 SomnukPhon-Amnuaisuk EvaluatingMelodicSegmentation...168 ChristianSpevak,BelindaThom,KarinHothker CombiningGrammar-BasedandMemory-BasedModelsofPerceptionof TimeSignatureandPhase ...183 NetaSpiro ABayesianApproachtoKey-Finding ...195 DavidTemperley AuthorIndex...207 StructureandInterpretationofMusicConcepts: MusicfromaComputationalPerspective MiraBalaban DepartmentofInformationSystemsEngineering Ben-GurionUniversityoftheNegev,Israel. mira@cs. bgu. ac. il Researchinthe?eldofComputer-Musicisdirectedtowardsconstructionof computersystemsforcomposition,performanceofmusicaltasks,musictra- ing,signalprocessingandextensionoftraditionalmusicsounds,notationstudy, musicanalysis,storageandcommunicationofmusicaldata,andmusicinf- mationretrievalandclassi?cation. Computerapplicationsinmusicleadtothe developmentofcomputationalmodels. ExamplesaretheworksofWinograd, Ebcioglu,Laske,Cope,Bamberger,Berger&GangandOrlarey. Berger&Gang usearti?cialneuralnetworkstoinvestigatemusicperception,Orlareyetal. - troducethenotionofConcreteAbstraction(borrowedfromLambdaCalculus) asabasisfortheirpurelyfunctionalcompositionenvironment,whileWinograd usesaSystemicGrammarapproachborrowedfromLinguistics. Inspiteofrichactivityinmusicologyandincomputermusic,thereislittle research(ifatall)onthedevelopmentofacomputationalbasisforcomputer music(e. g. ,Schenker,Narmour,LerdhalandJackendo?).Mostcomputermusic systemsindeedhavehugemusicalknowledgeandintuitionsembeddedinthem, butcannotpointonunderlyingexplicitcomputationalbasis. Clearlythey- sumesomelevelofprimitives,andusedi?erentabstractionlevelsandkinds,but thesearenotanchoredincomputationalmodelsthataccountfortheirbasics, organization,usageandsemantics. Inasense,thissituationremindsoneofthe earlydaysofNaturalLanguageProcessing,whenalargeamountoflinguistic knowledgewasembeddedinhugesemanticnetworks. Inthistalkweproposetoinitiateastudyofcomputationalframeworks formusicknowledge. Theideaistomakethemusicknowledgethatunderlies computer-musicapplications(eitherintentionallyornot)explicit. Asastarting point,wesuggesttostudy music schemas. HereishowMusicologistDahlia Cohen(dept. ofMusicology,HebrewUniversity,Israel)describestherolethat musicschemasplayinmusicunderstanding: Listeningtomusic(perceptionandreaction)anditsmemorization,are cognitiveactivitiesthatdependon schemas thatarecreated,unc- sciously,atanearlyage. Theschemasrepresentrelationshiptypes- tweenmusicaleventsthataredictatedbyprinciplesoforganization,in variousabstractionlevels. Theschemastriggerexpectationsthatmay ormaynotberealized.Musicisdistinguishedfromotherartsinhaving thesystematicorganizationasthesolemeansfortriggeringvarioustypes ofreactions(whereasotherartsemploynon-artistic,non-organizational meansforreactiontriggering).

Computational Creativity, Concept Invention, and General Intelligence in their own right all are flourishing research disciplines producing surprising and captivating results that continuously influence and change our view on where the limits of intelligent machines lie, each day pushing the boundaries a bit further. By 2014, all three fields also have left their marks on everyday life – machine-composed music has been performed in concert halls, automated theorem provers are accepted tools in enterprises’ R&D departments, and cognitive architectures are being integrated in pilot assistance systems for next generation airplanes. Still, although the corresponding aims and goals are clearly similar (as are the common methods and approaches), the developments in each of these areas have happened mostly individually within the respective community and without closer relationships to the goings-on in the other two disciplines. In order to overcome this gap and to provide a common platform for interaction and exchange between the different directions, the International Workshops on “Computational Creativity, Concept Invention, and General Intelligence” (C3GI) have been started. At ECAI-2012 and IJCAI-2013, the first and second edition of C3GI each gathered researchers from all three fields, presenting recent developments and results from their research and in dialogue and joint debates bridging the disciplinary boundaries. The chapters contained in this book are based on expanded versions of accepted contributions to the workshops and additional selected contributions by renowned researchers in the relevant fields. Individually, they give an account of the state-of-the-art in their respective area, discussing both, theoretical approaches as well as implemented systems. When taken together and looked at from an integrative perspective, the book in its totality offers a starting point for a (re)integration of Computational Creativity, Concept Invention,and General Intelligence, making visible common lines of work and theoretical underpinnings, and pointing at chances and opportunities arising from the interplay of the three fields.