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Turkish music generation using deep learning
Aydıngün, Anıl Bağdatlıoğlu, Denizcan Canbaz, Burak Kökbıyık, Abdullah Yavuz, M Furkan Bölücü, Necva Can, Burcu
Aydıngün, Anıl
Bağdatlıoğlu, Denizcan
Canbaz, Burak
Kökbıyık, Abdullah
Yavuz, M Furkan
Bölücü, Necva
Can, Burcu
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2021-01-07
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Abstract
Bu çalı¸smada derin ögrenme ile Türkçe ¸sarkı bes- ˘ teleme üzerine yeni bir model tanıtılmaktadır. ¸Sarkı sözlerinin Tekrarlı Sinir Agları kullanan bir dil modeliyle otomatik olarak ˘ olu¸sturuldugu, melodiyi meydana getiren notaların da benzer ˘ ¸sekilde nöral dil modeliyle olu¸sturuldugu ve sözler ile melodinin ˘ bütünle¸stirilerek ¸sarkı sentezlemenin gerçekle¸stirildigi bu çalı¸sma ˘ Türkçe ¸sarkı besteleme için yapılan ilk çalı¸smadır. In this work, a new model is introduced for Turkish song generation using deep learning. It will be the first work on Turkish song generation that makes use of Recurrent Neural Networks to generate the lyrics automatically along with a language model, where the melody is also generated by a neural language model analogously, and then the singing synthesis is performed by combining the lyrics with the melody. It will be the first work on Turkish song generation.
Citation
Aydıngün, A., Bağdatlıoğlu, D., Canbaz, B., Kökbıyık, A., Yavuz, M.F., Bölücü, N. and Can, B. (in press) Turkish music generation using deep learning, 28th IEEE 13th Signal Processing and Communications Applications Conference (SIU), 5th-7th October, 2020, Online.
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This is an accepted manuscript of an article published by IEEE in 28th IEEE Conference on Signal Processing and Communications Applications (SIU), available online at: https://ieeexplore.ieee.org/document/9302283
The accepted version of the publication may differ from the final published version.
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2165-0608