A Turkish makam music symbolic database for music information retrieval: SymbTr

Fecha de publicación

2016-01-29T10:32:17Z

2016-01-29T10:32:17Z

2012

Resumen

Turkish makam music needs a comprehensive database/nfor public consumption, to be used in MIR. This article/nintroduces SymbTr, a Turkish Makam Music Symbolic/nRepresentation Database, aimed at filling this void./nSymbTr consists of musical information in text, PDF, and/nMIDI formats. Raw data, drawn from reliable sources,/nand consisting of 1,700 musical pieces in Turkish art and/nfolk music was processed featuring distinct examples in/n155 diverse makams, 100 usuls and 48 forms. Special/ncare was devoted to selection of works that scatter across/na broad historical time span and were among those still/nperformed today. Total number of musical notes in these/npieces was 630,000, corresponding to a nominal playback/ntime of 72 hours. Synthesized sounds particular to Turkish/nmakam music were used in MIDI playback, and transcription//nplayback errors were corrected by input from/nexperts. Symbolic representation data, open to the public,/nis output from a computer program developed exclusively/nfor Turkish makam music. SymbTr was designed as a/nwholesome representation of aforementioned distinct auditory/nand visual features that distinguish Turkish makam/nmusic from other music genres. This article explains the/ndatabase format in detail, and also provides, through examples,/nstatistical information on pitch/interval allocation/nand distribution.


This research was partly funded by the European Research/nCouncil under the European Union's Seventh/nFramework Program, as part of the CompMusic project/n(ERC grant agreement 267583).

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International Society for Music Information Retrieval (ISMIR)

Documentos relacionados

Proceedings of 13th International Society for Music Information Retrieval Conference; 2012 October 8-12; Porto, Portugal. Porto: ISMIR, 2012. p. 223–228.

info:eu-repo/grantAgreement/EC/FP7/267583

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© 2012 International Society for Music Information Retrieval

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