Parameter Based Music Generation

Authors

  • Manav Bhanushali Student, Department of Computer Engineering, Sardar Patel Institute of Technology, Mumbai, India
  • Aryan Nathani Student, Department of Computer Engineering, Sardar Patel Institute of Technology, Mumbai, India
  • Sanimar Manghera Student, Department of Computer Engineering, Sardar Patel Institute of Technology, Mumbai, India
  • Jyoti Ramteke Professor, Department of Computer Engineering, Sardar Patel Institute of Technology, Mumbai, India
  • Chandrashekhar Gajbhiye Professor, Department of Computer Engineering, Sardar Patel Institute of Technology, Mumbai, India

Abstract

In this project, we propose a system for text-to-music generation, using AI techniques such as Natural Language Processing (NLP) and deep learning models. Our goal is to empower users to create music compositions using textual descriptions. The work is divided into three phases: literature survey, dataset preprocessing, and model implementation. This system makes music generation more accessible, even to users with no musical expertise, leveraging models such as LSTM, Bi-LSTM, and pre- trained models like MusicGen.

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Published

20-08-2025

Issue

Vol. 8 No. 8 (2025)

Section

Articles

License

Copyright (c) 2025 Manav Bhanushali, Aryan Nathani, Sanimar Manghera, Jyoti Ramteke, Chandrashekhar Gajbhiye

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
M. Bhanushali, A. Nathani, S. Manghera, J. Ramteke, and C. Gajbhiye, “Parameter Based Music Generation”, IJRESM, vol. 8, no. 8, pp. 35–37, Aug. 2025, Accessed: Aug. 29, 2025. [Online]. Available: https://journal.ijresm.com/index.php/ijresm/article/view/3336