Proposing the Application of LSTM Models to Create Music

In recent years, artificial intelligence (AI) and more specifically machine learning (ML) have emerged as a demonstration of the 4th industrial revolution. AI is present in all areas of human life from economics, education, and healthcare to housework, entertainment, and even the military. Outstanding applications in AI development come from many fields to solve different problems of life. The paper aims to learn and apply machine learning in sound processing for entertainment. In the paper, we use the long short-term memory (LSTM) model to create music. To perform the model, we have to collect data and preprocess to standardize the model training data. We then build a deep learning (DL) model using the LSTM network and train it with optimization parameters to create new, unique, and creative music. As a result, an automatic music generation model does not require human intervention and can generate highly rated music tracks based on the QoE factor as 5.15; 3.65; and 3.7 points for tracks 1, 2, and 3, respectively. The results show that the AI model has the potential to be applied in many areas of life.

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Publication Details

Published
2024-10-16
DOI
https://doi.org/10.1109/iconeei64414.2024.10747903
Primary Topic
Music Technology and Sound Studies
Type
article
Field-Weighted Citation Impact
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article

Proposing the Application of LSTM Models to Create Music

Bang Nguyen Anh, Nguyêñ Duy Tân, Xuyen Do Bui Thanh, Lam Nguyen Tan Phuc
Music Technology and Sound Studies
article

Proposing the Application of LSTM Models to Create Music

Bang Nguyen Anh, Nguyêñ Duy Tân, Xuyen Do Bui Thanh, Lam Nguyen Tan Phuc
article en

Abstract

In recent years, artificial intelligence (AI) and more specifically machine learning (ML) have emerged as a demonstration of the 4th industrial revolution. AI is present in all areas of human life from economics, education, and healthcare to housework, entertainment, and even the military. Outstanding applications in AI development come from many fields to solve different problems of life. The paper aims to learn and apply machine learning in sound processing for entertainment. In the paper, we use the long short-term memory (LSTM) model to create music. To perform the model, we have to collect data and preprocess to standardize the model training data. We then build a deep learning (DL) model using the LSTM network and train it with optimization parameters to create new, unique, and creative music. As a result, an automatic music generation model does not require human intervention and can generate highly rated music tracks based on the QoE factor as 5.15; 3.65; and 3.7 points for tracks 1, 2, and 3, respectively. The results show that the AI model has the potential to be applied in many areas of life.

Le Hong Phong High School for the Gifted (VN), Hanoi University of Science and Technology (VN)
Openalex Percentile: Top 80%
Music Technology and Sound Studies
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