Computational Modeling of Improvisation in Turkish Folk Music Using Variable-length Markov Models

نویسندگان

  • Sertan Şentürk
  • Parag Chordia
چکیده

The paper describes a new database, which currently consists of 64 songs encompassing approximately 6600 notes, and a system, which uses Variable-Length Markov Models (VLMM) to predict the melodies in the uzun hava (long tune) form, a melodic structure in Turkish folk music. The work shows VLMMs are highly predictive. This suggests that variable-length Markov models (VLMMs) may be applied to makam-based and non-metered musical forms, in addition to Western musical traditions [20]. To the best of our knowledge, the work presents the first symbolic, machine readable database and the first application of expressive modeling in Turkish folk music.

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تاریخ انتشار 2011