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