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Emotional Piano Melodies Generation Using Long Short-Term Memory

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Intelligent Information and Database Systems (ACIIDS 2021)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 12672))

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Abstract

One of the tremendous topics in the music industry is an automatic music composition. In this study, we aim to build an architecture that shows how LSTM models compose music using the four emotional piano datasets. The architecture consists of four steps: data collection, data preprocessing, training the models with one and two hundred epochs, and evaluation by loss analysis. From the result of this work, the model trained for 200 epochs give the lowest loss error rate for the composing of emotional piano music. Finally, we generate four emotional melodies based on the result.

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Acknowledgment

This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT & Future Planning (No. 2017R1A2B4010826), and (2019K2A9A2A06020672) and (No. 2020R1A2B5B02001717).

Author information

Authors and Affiliations

  1. Department of Computer Science, School of Electrical and Computer Engineering, Chungbuk National University, Cheongju, 28644, Korea

    Khongorzul Munkhbat, Bilguun Jargalsaikhan & Tsatsral Amarbayasgalan

  2. Faculty of Information Technology, Ton Duc Thang University, Ho Chi Minh City, 700000, Vietnam

    Keun Ho Ryu

  3. Biomedical Engineering Institute, Chiang Mai University, Chiang Mai, 50200, Thailand

    Nipon Theera-Umpon & Keun Ho Ryu

  4. Department of Electrical Engineering, Faculty of Engineering, Chiang Mai University, Chiang Mai, 50200, Thailand

    Nipon Theera-Umpon

Authors
  1. Khongorzul Munkhbat
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  2. Bilguun Jargalsaikhan
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  3. Tsatsral Amarbayasgalan
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  4. Nipon Theera-Umpon
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  5. Keun Ho Ryu
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Corresponding author

Correspondence to Keun Ho Ryu .

Editor information

Editors and Affiliations

  1. Wrocław University of Science and Technology, Wrocław, Poland

    Ngoc Thanh Nguyen

  2. King Mongkut's Institute of Technology Ladkrabang, Bangkok, Thailand

    Suphamit Chittayasothorn

  3. Nanyang Technological University, Singapore, Singapore

    Dusit Niyato

  4. Wrocław University of Science and Technology, Wrocław, Poland

    Bogdan Trawiński

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Munkhbat, K., Jargalsaikhan, B., Amarbayasgalan, T., Theera-Umpon, N., Ryu, K.H. (2021). Emotional Piano Melodies Generation Using Long Short-Term Memory. In: Nguyen, N.T., Chittayasothorn, S., Niyato, D., Trawiński, B. (eds) Intelligent Information and Database Systems. ACIIDS 2021. Lecture Notes in Computer Science(), vol 12672. Springer, Cham. https://doi.org/10.1007/978-3-030-73280-6_53

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  • DOI: https://doi.org/10.1007/978-3-030-73280-6_53

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-73279-0

  • Online ISBN: 978-3-030-73280-6

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