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Recent advancements in generative models have shown remarkable progress inmusic generation. However, most existing methods focus on generating monophonicor homophonic music, while the generation of polyphonic and multi-track musicwith rich attributes is still a challenging task. In this paper, we propose anovel approach for multi-track, multi-attribute symphonic music generationusing the diffusion model. Specifically, we generate piano-roll representationswith a diffusion model and map them to MIDI format for output. To capture richattribute information, we introduce a color coding scheme to encode notesequences into color and position information that represents pitch,velocity,and instrument. This scheme enables a seamless mapping between discrete musicsequences and continuous images. We also propose a post-processing method tooptimize the generated scores for better performance. Experimental results showthat our method outperforms state-of-the-art methods in terms of polyphonicmusic generation with rich attribute information compared to the figuremethods.

DiffuseRoll: Multi-track multi-category music generation based on diffusion model