Papers › Quality-aware Masked Diffusion Transformer for Enhanced Music Generation
Quality-aware Masked Diffusion Transformer for Enhanced Music Generation
Chang Li, Ruoyu Wang, Lijuan Liu, Jun Du, Yixuan Sun, Zilu Guo, Zhenrong Zhang, Yuan Jiang, Jianqing Gao, Feng Ma
Text-to-music (TTM) generation, which converts textual descriptions into audio, opens up innovative avenues for multimedia creation. Achieving high quality and diversity in this process demands extensive, high-quality data, which are often scarce in available datasets. Most open-source datasets frequently suffer from issues like low-quality waveforms and low text-audio consistency, hindering the advancement of music generation models. To address these challenges, we propose a novel quality-aware training paradigm for generating high-quality, high-musicality music from large-scale, quality-imbalanced datasets. Additionally, by leveraging unique properties in the latent space of musical signals, we adapt and implement a masked diffusion transformer (MDT) model for the TTM task, showcasing its capacity for quality control and enhanced musicality. Furthermore, we introduce a three-stage caption refinement approach to address low-quality captions' issue. Experiments show state-of-the-art (SOTA) performance on benchmark datasets including MusicCaps and the Song-Describer Dataset with both objective and subjective metrics. Demo audio samples are available at https://qa-mdt.github.io/, code and pretrained checkpoints are open-sourced at https://github.com/ivcylc/OpenMusic.
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Code
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Code Syntology ran Syntology
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Music Generation | Song Describer Dataset | OpenMusic | FAD VGG | 1.01 | #1 of 1 | Archive leaderboard | report |
| Text-to-Music Generation | MusicCaps | OpenMusic (QA-MDT) | FAD | 1.65 | #3 of 21 | Archive leaderboard | report |
| Text-to-Music Generation | MusicCaps | OpenMusic (QA-MDT) | IS | 2.80 | #3 of 21 | Archive leaderboard | report |
| Text-to-Music Generation | MusicCaps | OpenMusic (QA-MDT) | KL_passt | 1.31 | #3 of 21 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
Methods
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