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Linking Scores and Audio Recordings in Makam Music of Turkey
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: Journal for New Music Research, ISSN 0929-8215, Vol. 43, no 1, 34-52 p.Article in journal (Refereed) Published
Abstract [en]

The most relevant representations of music are notations and audio recordings, each of which emphasizes a particular perspective and promotes different approximations in the analysis and understanding of music. Linking these two representations and analysing them jointly should help to better study many musical facets by being able to combine complementary analysis methodologies. In order to develop accurate linking methods, we have to take into account the specificities of a given type of music. In this paper, we present a method for linking musically relevant sections in a score of a piece from makam music of Turkey (MMT) to the corresponding time intervals of an audio recording of the same piece. The method starts by extracting relevant features from the score and from the audio recording. The features of a given score section are compared with the features of the audio recording to find the candidate links in the audio for that score section. Next, using the sequential section information stored in the score, it selects the most likely links. The method is tested on a dataset consisting of instrumental and vocal compositions of MMT, achieving 92.1% and 96.9% F-1-scores on the instrumental and vocal pieces, respectively. Our results show the importance of culture-specific and knowledge-based approaches in music information processing.

Place, publisher, year, edition, pages
Taylor & Francis Group, 2014. Vol. 43, no 1, 34-52 p.
Keyword [en]
culture specificity, directed acyclic graphs, Hough transform, knowledge-based methodologies, makam music of Turkey, multi-modality, music information retrieval, variable-length Markov models
National Category
Media and Communication Technology
Research subject
Speech and Music Communication; Media Technology
Identifiers
URN: urn:nbn:se:kth:diva-193731DOI: 10.1080/09298215.2013.864681ISI: 000334075500004Scopus ID: 2-s2.0-84897448696OAI: oai:DiVA.org:kth-193731DiVA: diva2:1040446
Funder
EU, FP7, Seventh Framework Programme, 267583
Note

QC 20161027

Available from: 2016-10-27 Created: 2016-10-10 Last updated: 2018-01-14Bibliographically approved

Open Access in DiVA

fulltext(11334 kB)