Versatile Framework for Song Generation with Prompt-based Control

• URL: http://arxiv.org/abs/2504.19062v2
• Date: Tue, 29 Apr 2025 09:19:41 GMT
• Title: Versatile Framework for Song Generation with Prompt-based Control
• Authors: Yu Zhang, Wenxiang Guo, Changhao Pan, Zhiyuan Zhu, Ruiqi Li, Jingyu Lu, Rongjie Huang, Ruiyuan Zhang, Zhiqing Hong, Ziyue Jiang, Zhou Zhao,
• Abstract summary: VersBand is a framework for synthesizing high-quality, aligned songs with prompt-based control.<n>VocalBand, a decoupled model, leverages the flow-matching method for generating singing styles, pitches, and mel-spectrograms.<n>AccompBand, a flow-based transformer model, incorporates the Band-MOE, selecting suitable experts for enhanced quality, alignment, and control.<n>Two generation models, LyricBand for lyrics and MelodyBand for melodies, contribute to the comprehensive multi-task song generation system.
• Score: 50.359999116420084
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Song generation focuses on producing controllable high-quality songs based on various prompts. However, existing methods struggle to generate vocals and accompaniments with prompt-based control and proper alignment. Additionally, they fall short in supporting various tasks. To address these challenges, we introduce VersBand, a multi-task song generation framework for synthesizing high-quality, aligned songs with prompt-based control. VersBand comprises these primary models: 1) VocalBand, a decoupled model, leverages the flow-matching method for generating singing styles, pitches, and mel-spectrograms, allowing fast, high-quality vocal generation with style control. 2) AccompBand, a flow-based transformer model, incorporates the Band-MOE, selecting suitable experts for enhanced quality, alignment, and control. This model allows for generating controllable, high-quality accompaniments aligned with vocals. 3) Two generation models, LyricBand for lyrics and MelodyBand for melodies, contribute to the comprehensive multi-task song generation system, allowing for extensive control based on multiple prompts. Experimental results demonstrate that VersBand performs better over baseline models across multiple song generation tasks using objective and subjective metrics. Audio samples are available at https://aaronz345.github.io/VersBandDemo.

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