Synthesis of Turkish Makam Music Scores Using An Adaptive Tuning Approach
| Main Authors: | Atlı, Hasan Sercan, Şentürk, Sertan, Bozkurt, Barış, Serra, Xavier |
|---|---|
| Format: | Proceeding |
| Terbitan: |
, 2017
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| Subjects: | |
| Online Access: |
https://zenodo.org/record/580743 |
| ctrlnum |
580743 |
|---|---|
| fullrecord |
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<dc schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><creator>Atlı, Hasan Sercan</creator><creator>Şentürk, Sertan</creator><creator>Bozkurt, Barış</creator><creator>Serra, Xavier</creator><date>2017-06-14</date><description>Music synthesis is one of the most essential features of music notation software and applications aimed at navigating digital music score libraries. Currently, the majority of music synthesis tools are designed for Eurogenetic musics, and they are not able to address the culture-specific aspects (such as tuning, intonation and timbre) of many music cultures. In this paper, we focus on the tuning dimension in musical score playback for Turkish Makam Music (TMM). Based on existing computational tuning analysis methodologies, we propose an automatic synthesis methodology, which allows the user to listen to a music score synthesized according to the tuning extracted from an audio recording. As a proof-of-concept, we also present a desktop application, which allows the users to listen to playback of TMM music scores according to the theoretical temperament or a user specified reference recording. The playback of the synthesis using the tuning extracted from the recordings may provide a better user experience, and it may be used to assist music education, enhance music score editors and complement research in computational musicology.</description><identifier>https://zenodo.org/record/580743</identifier><identifier>10.5281/zenodo.580743</identifier><identifier>oai:zenodo.org:580743</identifier><relation>info:eu-repo/grantAgreement/EC/FP7/267583/</relation><rights>info:eu-repo/semantics/openAccess</rights><rights>https://creativecommons.org/licenses/by/4.0/legalcode</rights><subject>score synthesis</subject><subject>audio tuning analysis</subject><subject>Turkish makam music</subject><subject>predominant melody extraction</subject><subject>tonic identification</subject><subject>Karplus-Strong string model</subject><subject>MusicXML</subject><title>Synthesis of Turkish Makam Music Scores Using An Adaptive Tuning Approach</title><type>Journal:Proceeding</type><type>Journal:Proceeding</type><recordID>580743</recordID></dc>
|
| format |
Journal:Proceeding Journal |
| author |
Atlı, Hasan Sercan Şentürk, Sertan Bozkurt, Barış Serra, Xavier |
| title |
Synthesis of Turkish Makam Music Scores Using An Adaptive Tuning Approach |
| publishDate |
2017 |
| topic |
score synthesis audio tuning analysis Turkish makam music predominant melody extraction tonic identification Karplus-Strong string model MusicXML |
| url |
https://zenodo.org/record/580743 |
| contents |
Music synthesis is one of the most essential features of music notation software and applications aimed at navigating digital music score libraries. Currently, the majority of music synthesis tools are designed for Eurogenetic musics, and they are not able to address the culture-specific aspects (such as tuning, intonation and timbre) of many music cultures. In this paper, we focus on the tuning dimension in musical score playback for Turkish Makam Music (TMM). Based on existing computational tuning analysis methodologies, we propose an automatic synthesis methodology, which allows the user to listen to a music score synthesized according to the tuning extracted from an audio recording. As a proof-of-concept, we also present a desktop application, which allows the users to listen to playback of TMM music scores according to the theoretical temperament or a user specified reference recording. The playback of the synthesis using the tuning extracted from the recordings may provide a better user experience, and it may be used to assist music education, enhance music score editors and complement research in computational musicology. |
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2022-06-06T04:23:04Z |
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