Diziden Diziye Modeli ve MIDI Müzik Veri Tabanı Kullanımıyla Gerçekçi Bir Davul Eşliği Üreteci

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Date

2022

Authors

Gumustekin, Sevket

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IEEE

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Green Open Access

No

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Abstract

In this work, artificial intelligence reinterpretation and/or addition of drum parts for musical pieces supplied in Musical Instruments Digital Interface (MIDI) format, have been carried out. To achieve this, Sequence-to-Sequence learning method and Encoder-Decoder Long Short-Term Memory (LSTM) artificial neural network model have been used. In order to improve training of this neural network, teacher forcing method was utilized. In the generation of new drum parts, the quality and the originality of the samples were improved by using temperature sampling. Our proposed method produces high quality drum accompaniments with adjustable complexity.

Description

Keywords

Midi, Sequence-To-Sequence, Encoder And Decoder, Long-Short Term Memory, Teacher Forcing, Temperature Sampling, Autonomous Music Accompany

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1

Source

30th IEEE Signal Processing and Communications Applications Conference (SIU) -- MAY 15-18, 2022 -- Safranbolu, TURKEY

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1

End Page

4
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1

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593

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248

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