Transfer Learning for Underrepresented Music Generation

Anahita Doosti; Matthew Guzdial

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arXiv · 2306.00281

Transfer Learning for Underrepresented Music Generation

Anahita Doosti·Matthew Guzdial

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Abstract

This paper investigates a combinational creativity approach to transfer learning to improve the performance of deep neural network-based models for music generation on out-of-distribution (OOD) genres. We identify Iranian folk music as an example of such an OOD genre for MusicVAE, a large generative music model. We find that a combinational creativity transfer learning approach can efficiently adapt MusicVAE to an Iranian folk music dataset, indicating potential for generating underrepresented music genres in the future.

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Anahita Doosti, Matthew Guzdial. 2023-06-01. Transfer Learning for Underrepresented Music Generation. https://arxiv.org/abs/2306.00281

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