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 ...
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.
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