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Style-Specific Turkish Pop Music Composition with CNN and LSTM Network  
Yazarlar (2)
Dr. Öğr. Üyesi Senem TANBERK Dr. Öğr. Üyesi Senem TANBERK
x, Türkiye
Dilek Bilgin Tükel
Doğuş, Türkiye
Devamını Göster
Özet
The recent advance in artificial neural networks is an inspiration for automatic music generation. Deep learning algorithms help to produce pleasing melodies. They lead the creativity of musicians to be reproduced in digital environments. The proposed system learns from the Turkish popular music and then produces new music. In this study, our goal is to generate melody with a specific style, such as unforgettable soundtracks admired widely. We proposed a novel combination of convolutional neural network (CNN) and long short-term memory (LSTM) network for music generation. The experimental results reveal that the proposed combined deep model exhibits remarkable music quality compared to the lstm-only deep model or cnn-only deep model. We also conducted a survey to evaluate the quality of the generated music. The survey results show that the introduced model is capable of producing better quality …
Anahtar Kelimeler
Bildiri Türü Tebliğ/Bildiri
Bildiri Alt Türü Tam Metin Olarak Yayınlanan Tebliğ (Uluslararası Kongre/Sempozyum)
Bildiri Niteliği Alanında Hakemli Uluslararası Kongre/Sempozyum
Bildiri Dili İngilizce
Kongre Adı 2021 IEEE 19th World Symposium on Applied Machine Intelligence and Informatics (SAMI)
Kongre Tarihi 21-01-2021 / 21-01-2021
Basıldığı Ülke Türkiye
Basıldığı Şehir
Atıf Sayıları
Google Scholar 13

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