Uyar, BurakAtli, Hasan SercanSentürk, SertanBozkurt, BarisSerra, Xavier2018-08-272018-08-272014Uyar B, Atli HS, Şentürk S, Bozkurt B, Serra X. A corpus for computational research of Turkish Makam music. In: Proceedings of the 1st International workshop on Digial Libraries for Musicology; 2014 Sept 12; London, UK. London: ACM; 2014. 7 p. DOI: 10.1145/2660168.2660174http://hdl.handle.net/10230/35358Comunicació presentada al 1st International workshop on Digial Libraries for Musicology, que va tenir lloc el 12 de setembre de 2014 a Longres, Regne Unit.Each music tradition has its own characteristics in terms of melodic, rhythmic and timbral properties as well as semantic understandings. To analyse, discover and explore these culture-specific characteristics, we need music collections which are representative of the studied aspects of the music tradition. For Turkish makam music, there are various resources available such as audio recordings, music scores, lyrics and editorial metadata. However, most of these resources are not typically suited for computational analysis, are hard to access, do not have sufficient quality or do not include adequate descriptive information. In this paper we present a corpus of Turkish makam music created within the scope of the CompMusic project. The corpus is intended for computational research and the primary considerations during the creation of the corpus reflect some criteria, namely, purpose, coverage, completeness, quality and re-usability. So far, we have gathered approximately 6000 audio recordings, 2200 music scores with lyrics and 27000 instances of editorial metadata related to Turkish makam music. The metadata include information about makams, recordings, scores, compositions, artists etc. as well as the interrelations between them. In this paper, we also present several test datasets of Turkish makam music. Test datasets contain manual annotations by experts and they provide ground truth for specific computational tasks to test, calibrate and improve the research tools. We hope that this research corpus and the test datasets will facilitate academic studies in several fields such as music information retrieval and computational musicology.application/pdfeng© 2014 Association for Computing Machineryinfo:eu-repo/semantics/conferenceObjecthttp://dx.doi.org/10.1145/2660168.2660174info:eu-repo/semantics/openAccess