synthesis of turkish makam music scores using an … · bozkurt, b. (2008). an automatic pitch...

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SYNTHESIS OF TURKISH MAKAM MUSIC SCORES USING AN ADAPTIVE TUNING APPROACH Hasan Sercan Atlı Music Technology Group, UPF [email protected] Sertan Şentürk Music Technology Group, UPF [email protected] Barış Bozkurt University of Crete [email protected] Xavier Serra Music Technology Group, UPF [email protected] The 7th International Workshop on Folk Music Analysis 14~16 June, Malaga

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SYNTHESISOFTURKISHMAKAMMUSICSCORESUSINGANADAPTIVETUNINGAPPROACH

HasanSercan AtlıMusicTechnologyGroup,[email protected]

Sertan ŞentürkMusicTechnologyGroup,UPF

[email protected]

Barış BozkurtUniversity ofCrete

[email protected]

XavierSerraMusicTechnologyGroup,UPF

[email protected]

The7thInternationalWorkshoponFolkMusicAnalysis14~16June,Malaga

1. Introduction2. TurkishMakamMusic3. Methodology4. Applications5. Conclusion

Outline

• Scoresynthesis isoneofanimportantfeature– Providesreal-timeauralfeedbackonhowthenotatedmusic

wouldsoundlike.

• Mostofthesynthesistoolsrendertheaudiodevoidoftheperformanceaddedexpression.– Scoresofmanymusicculturesdonotexplicitlyinclude

importantinformationrelatedtoperformanceaspects.• Timing,dynamics,tuning,temperamentandetc.

Introduction

• NotationeditorsarecurrentlydesignedforEurogenetic music– 12tone-equal-tempered(TET)tuningsystem– Limitedsupportforintermediatetonesandmicrotonalintervals

• Maynegativelyimpactthemusiccreationprocess– Itmightevenleadtolossofsomevariationsintheexpression

andunderstandingofthemusiccultureinthelongterm

Introduction

• AdaptiveSynthesis- Allowstheusertosynthesizethemelodyinamusicscore– accordingtoagiventuningsystem– accordingtothetuningextractedfromaudiorecordings

• Tuningandtemperamentdimensionsinmusicscoresynthesis,specificallyforTurkishmakam music– Consistsofdiversetuningsandmicrotonalintervals,whichvary

withrespecttothemakam (melodicstructure),geographicalregionandartists

Introduction

compmusic.upf.edu/node/339

1. Introduction2. TurkishMakam Music

– Makam andKarar (tonic)– MainstreamTheory,Arel-Ezgi-Uzdilek (AEU)– SymbTr ScoreCollection

3. Methodology4. Applications5. Conclusion

Outline

2.TurkishMakamMusicMakam andKarar (tonic)

8

• Melodicdimensionexplainedbymakams– Melodiesrevolvearoundasomemelodiccenters– Finaltone≈Tonic

• Nodefinitetuningreference(e.g.A4=440Hz)• Diversetuning&intonation• Allowsahighdegreeofexpressivity

2.TurkishMakamMusicMainstreamtheory,Arel-Ezgi-Uzdilek (AEU)

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• IMPORTANT: Theoriesdoesnotnecessarilycorrespondtothepractice

• Arel-Ezgi-Uzdilek isthemainstreammusicaltheory– 24notesinanoctave– Awholetoneisdividedinto9Holderian commas(Hc)– Approximationof53tone-equal-tempered(TET)system

• 1Hc ≈22.6cents.

2.TurkishMakamMusicSymbTr ScoreCollectionv2.4.3

10

M.KemalKaraosmanoğlu.ATurkishmakammusicsymbolicdatabaseformusicinformationretrieval:SymbTr.InProceedingsof13thInternationalSocietyforMusicInformationRetrievalConference(ISMIR),pages223–228,2012.

LyricsNoteSymbols

Duration

Gün doğ ma dan a ca nım görü şelim giz li ce SAZ . . .

• Thelargestandmostrepresentativemachine-readablescorecollectionofTurkishmakam music(2200musicscores)

https://github.com/MTG/SymbTr/

• Availableindifferentformats

1. Introduction2. TurkishMakamMusic

3. Methodology– Predominantmelodyextraction– Tonicidentification– Tuninganalysisandadaptation– Scoresynthesis

5. Applications6. Conclusion

Outline

3.Methodology

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AudioRecording PredominantMelodyExtraction

PitchDistributionTonicFrequencyIdentification

MachineReadableScore

Tuningadaptation&Synthesis

3.MethodologyAudioRecording PredominantMelodyExtraction

3.MethodologyPredominantMelodyExtraction

14

J.Salamon andE.Gómez,"MelodyExtractionfromPolyphonicMusicSignalsusingPitchContourCharacteristics",IEEETransactionsonAudio,SpeechandLanguageProcessing,20(6):1759-1770,Aug.2012.

3.MethodologyPredominantMelodyExtraction

15

Atlı,H.S.,Uyar,B.,Şentürk,S.,Bozkurt,B.,andSerra,X.(2014).AudiofeatureextractionforexploringTurkishmakammusic.InProceedings of3rdInternationalConferenceon AudioTechnologiesforMusicandMedia,pages142–153,Ankara,Turkey.

https://github.com/sertansenturk/predominantmelodymakam

3.Methodology

16

AudioRecording PredominantMelodyExtraction

PitchDistribution

3.MethodologyPitchDistributionComputation

17

Frekans (Hz)

Görü

lme Sık

lığı Tepe noktası

Chordia, P. & Şentürk, S. (2013). Joint recognition of raag and tonic in North Indian music. Computer Music Journal, 37(3).

Bozkurt, B. (2008). An automatic pitch analysis method for Turkish maqam music. Journal of New Music Research, 37(1), 1–13.

https://github.com/altugkarakurt/morty

3.Methodology

18

AudioRecording PredominantMelodyExtraction

PitchDistributionTonicFrequencyIdentification

3.MethodologyTonicIdentification

19

Atlı,H.S.,Bozkurt B.,&Şentürk S.(2015).AmethodfortonicfrequencyidentificationofTurkishmakammusicrecordings.5thInternationalWorkshoponFolkMusicAnalysis(FMA).119-122.

https://github.com/hsercanatli/tonicidentifier_makam

3.Methodology

20

AudioRecording PredominantMelodyExtraction

PitchDistributionTonicFrequencyIdentification

MachineReadableScore

3. MethodologyTuning analysis and adaptation

21

PitchDistribution TonicFrequencyIdentification

Frequency

Occurrence

https://github.com/miracatici/notemodel

Makam information,notes&scalecomesfrommusicscore

TuningAdapter

3. MethodologySynthesis

22

Frequency

Occurrence

https://github.com/hsercanatli/symbtrsynthesis

Synthesizedscore

MachineReadableScore

AdaptedTuning

Synthesizer

1. Introduction2. Motivation3. TurkishMakamMusic4. Methodology5. Applications

– Dunya &Dunya-web– Dunya-desktop– Application:Dunya-desktopAdaptiveSynthesisExtension

6. Conclusion

Outline

5. ApplicationsDunya & Dunya-web

24

Dunya-web

API2200~7000>22000

dunya.compmusic.upf.edu

>190gb

5. ApplicationsDunya-desktop

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https://github.com/MTG/dunya-desktop

5. ApplicationsDunya-desktop Adaptive Synthesis Extension

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https://github.com/MTG/dunya-desktop/tree/adaptive-synthesis

5. ApplicationsDunya-desktop Adaptive Synthesis Extension - Dataset

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• 5Makams (Hicaz,Nihavent,UşşakRastandHüzzam)– Covers25%ofSymbTr Scorecollection

• 10“good-quality”recordingsforeachmakam– 50tuningpresets

• Includes;– Metadata– Predominantmelody– Pitchdistribution– Notemodels

https://github.com/MTG/otmm_tuning_intonation_dataset

• Presentedamethodologyforscoresynthesis• Developedadesktopapplication

• Futureworks– Conductuserstudies– Improvethesynthesismethodology withscore-informedtuning&intonation

analysis

Conclusion

Şentürk,S.(2016).ComputationalAnalysisofAudioRecordingsandMusicScoresfortheDescriptionandDiscoveryofOttoman-TurkishMakamMusic.PhDthesis,UniversitatPompeuFabra,Barcelona.

Companionpage:compmusic.upf.edu/node/339

Thankyou!