Style-Specific Turkish Pop Music Composition with CNN and LSTM Network

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Institute of Electrical and Electronics Engineers Inc.

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info:eu-repo/semantics/closedAccess

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 and more pleasant music compared to other state-of-the-art music generation methods. © 2021 IEEE.

Açıklama

IEEE Control Systems Chapter;IEEE Hungary Section;IEEE Joint Chapter of IES and RAS;IEEE SMC Chapter

Anahtar Kelimeler

automation; convolutional neural network; deep learning; long short-term memory; music generation

Kaynak

SAMI 2021 - IEEE 19th World Symposium on Applied Machine Intelligence and Informatics, Proceedings
19th IEEE World Symposium on Applied Machine Intelligence and Informatics, SAMI 2021 -- 21 January 2021 through 23 January 2021 -- -- 168037

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