Deep learning for Turkish makam music composition

Parlak, İsmail Hakkı; Çebi, Yalçın; Işıkhan, Cihan; Birant, Derya

doi:10.3906/elk-2101-44

Cited by 5 publications

(2 citation statements)

References 13 publications

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“…Others are on the same page as LSTMs are also used in other papers such as BachProp by Colombo & Gertsner (2018), and other works concerning music generation. In line with this, Parlak et al (2021), Chu et al (2017), andSimon &Oore's (2017) papers use piano music as the baseline instrument in their midi files. The midi files as well vary between papers.…”

Section: Deep Learning For Music Compositionmentioning

confidence: 90%

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Pop Music Midi Generation using Long Short-Term Memory based Recurrent Neural Network

Ignacio,

Sicangco,

Esquivel

2023

Proceedings of the International Conference on Industrial Engineering and Operations Management

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As music composition and technology grow, the pursuit for music creation with machine learning as a trans-human collaborator is a relatively new venture in the world of artificial intelligence. Various RNN models for music genres such as classical, folk, and jazz has been made but none specifically for pop music. The study aims to fill in this gap. A pop music dataset was created from Billboards' Hot 100 Year End Charts of 2021. The dataset was used to train LSTM-based RNN models which were then evaluated through loss. This revealed that the model with the lowest loss came from the ADAM optimizer making it the best choice with 200 epochs. The results of the chosen model were then evaluated through its perplexity and a listening test. With a low perplexity score, the model was deemed confident in creating novel midi samples. The listening test then tested the created midi samples, resulting in a good rating.

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Section: Deep Learning For Music Compositionmentioning

confidence: 90%

“…Multiple papers have been created from Google's endeavor. These include the Turkish makam music composition by Parlak et al (2021), Song from Pi by Chu et al (2017) and other music related research that take Magenta as relevant literature.…”

Section: Deep Learning For Music Compositionmentioning

confidence: 99%

Pop Music Midi Generation using Long Short-Term Memory based Recurrent Neural Network

Ignacio,

Sicangco,

Esquivel

2023

Proceedings of the International Conference on Industrial Engineering and Operations Management

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Music Deep Learning: Deep Learning Methods for Music Signal Processing—A Review of the State-of-the-Art

et al. 2023

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The discipline of Deep Learning has been recognized for its strong computational tools, which have been extensively used in data and signal processing, with innumerable promising results. Among the many commercial applications of Deep Learning, Music Signal Processing has received an increasing amount of attention over the last decade. This work reviews the most recent developments in Deep Learning in Music signal processing. Two main applications that are discussed are Music Information Retrieval, which spans a plethora of applications, and Music Generation, which can fit a range of musical styles. After a review of both topics, several emerging directions are identified for future research.

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