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Section-level modeling of musical audio for linking performances to scores in Turkish makam music
Bogazici University, Turkey.ORCID iD: 0000-0003-1679-6018
2015 (English)In: Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), IEEE conference proceedings, 2015, 141-145 p.Conference paper (Refereed)
Abstract [en]

Section linking aims at relating structural units in the notation of a piece of music to their occurrences in a performance of the piece. In this paper, we address this task by presenting a score-informed hierarchical Hidden Markov Model (HHMM) for modeling musical audio signals on the temporal level of sections present in a composition, where the main idea is to explicitly model the long range and hierarchical structure of music signals. So far, approaches based on HHMM or similar methods were mainly developed for a note-to-note alignment, i.e. an alignment based on shorter temporal units than sections. Such approaches, however, are conceptually problematic when the performances differ substantially from the reference score due to interpretation and improvisation, a very common phenomenon, for instance, in Turkish makam music. In addition to having low computational complexity compared to note-to-note alignment and achieving a transparent and elegant model, the experimental results show that our method outperforms a previously presented approach on a Turkish makam music corpus.

Place, publisher, year, edition, pages
IEEE conference proceedings, 2015. 141-145 p.
Series
, ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, ISSN 1520-6149
Keyword [en]
Audio-to-score alignment; Section linking; Hierarchical hidden Markov models; Turkish makam music
National Category
Media Engineering
Research subject
Computer Science; Media Technology; Speech and Music Communication
Identifiers
URN: urn:nbn:se:kth:diva-193750DOI: 10.1109/ICASSP.2015.7177948ISI: 000368452400029ScopusID: 2-s2.0-84946075548ISBN: 978-146736997-8OAI: oai:DiVA.org:kth-193750DiVA: diva2:1040424
Conference
IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)
Note

QC 20161031

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

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Holzapfel, André
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