Papers with music generation
Music for All: Representational Bias and Cross-Cultural Adaptability of Music Generation Models (2025.findings-naacl)
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| Challenge: | Existing music generation models are limited in their coverage of the musical genres and cultures of the world. |
| Approach: | They propose to use parametric fine tuning techniques to mitigat the bias in existing music datasets. |
| Outcome: | The proposed models are able to perform well across genres and cultures. |
Text-to-Song: Towards Controllable Music Generation Incorporating Vocal and Accompaniment (2024.acl-long)
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Zhiqing Hong, Rongjie Huang, Xize Cheng, Yongqi Wang, Ruiqi Li, Fuming You, Zhou Zhao, Zhimeng Zhang
| Challenge: | Existing studies focus on singing voice synthesis and music generation independently. |
| Approach: | They propose a novel task called Text-to-Song synthesis which incorporates both vocal and accompaniment generation. |
| Outcome: | The proposed method can synthesize songs with comparable quality and style consistency. |
AudioStealer: Extracting Audio Prompts via Shapley Value-Guided Query Search (2026.findings-acl)
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| Challenge: | prompt stealing is a new form of attack that aims to reconstruct high-value prompts that guide music generation. |
| Approach: | They propose a method to steal music prompts from audio domains using a black-box attack framework. |
| Outcome: | The proposed method recovers prompts with high textual consistency to the ground truth while maintaining strong perceptual similarity to the target recordings. |