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Incorporating pitch class profiles for improving automatic transcription of Turkish makam music
KTH, School of Computer Science and Communication (CSC), Media Technology and Interaction Design, MID. (Sound and Music Computing)ORCID iD: 0000-0003-1679-6018
2014 (English)In: Proceedings of the 4th Workshop on Folk Music Analysis, Computer Engineering Department, Bogaziçi University , 2014, 15-20 p.Conference paper (Refereed)
Abstract [en]

In this paper we evaluate the impact of including knowledge about scale material into a system for the transcription of Turkish makam music. To this end, we extend our previously presented appoach by a refinement iteration that gives preference to note values present in the scale of the mode (i.e. makam). The information about the scalar material is provided in form of pitch class profiles, and they are imposed in form of a Dirichlet prior to our expanded probabilistic latent component analysis (PLCA) transcription system. While the inclusion of such a prior was supposed to focus the transcription system on musically meaningful areas, the obtained results are significantly improved only for recordings of certain instruments. In our discussion we demonstrate the quality of the obtained transcriptions, and discuss the difficulties caused for evaluation in the context of microtonal music.

Place, publisher, year, edition, pages
Computer Engineering Department, Bogaziçi University , 2014. 15-20 p.
Keyword [en]
Automatic music transcription, pitch profiles
National Category
Media and Communication Technology
Research subject
Computer Science; Media Technology; Speech and Music Communication
Identifiers
URN: urn:nbn:se:kth:diva-193733OAI: oai:DiVA.org:kth-193733DiVA: diva2:1040442
Conference
FMA 2014, 4th Workshop on Folk Music Analysis
Note

QC 20161031

Available from: 2016-10-27 Created: 2016-10-10 Last updated: 2016-11-10Bibliographically approved

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Holzapfel, André
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Media Technology and Interaction Design, MID
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