Music Generation through Transformers

Authors

  • Shubhham Agarwal Liverpool John Moores University
  • Nailya Sultanova Kazan Federal University, Russia

DOI:

https://doi.org/10.69511/ijdsaa.v6i6.231

Keywords:

Music Generation, Transformer, Artificial Intelligence, Composer, Machine Learning Models, Deep Learning models

Abstract

The content creator industry has been booming. After COVID-19 hit, the way content was observed changed drastically within the people using the social media platforms like Instagram, Facebook, Twitter, Tik Tok etc. There is an entire profession of “Influencers” who have become public figures due to their videos which are educational, or influencing the day to day decisions through reviews/unboxing or are just blogs/vlogs about passionate topics like traveling, food etc. This rise in video content has pushed the need for background music as well as the content creators are constantly adding in the videos with fresh, engaging music which sets the mood of the videos. True message is conveyed only when the music supporting the video matches with the mood of the viewers. The challenge is that music composition, editing etc. is a professional job and the influencers may not necessarily have those skills. Content creators can either try to create their own music which may have some transitional gaps or the quality of music may suffer or they can now buy the music through a licensing platform. In this research, transformers will be used to generate the transitional music for mixing two different sound clips.

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Published

2024-06-15

How to Cite

Agarwal, S. ., & Sultanova, N. (2024). Music Generation through Transformers. International Journal of Data Science and Advanced Analytics, 6(1), 302–306. https://doi.org/10.69511/ijdsaa.v6i6.231

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Section

Articles