🤖 AI Summary
To address limitations in creative generation, structural organization, and human-AI collaboration in multi-track electronic music composition, this paper introduces TOMI—a novel framework that pioneers a sparse four-dimensional representation integrating conceptual hierarchy and spatiotemporal structure (segment–section–track–transformation operation), enabling end-to-end composition via instruction-tuned large language models. TOMI unifies MIDI/audio generation and conversion techniques to synthesize full-song multi-track arrangements and natively integrates with the REAPER digital audio workstation. Experimental evaluations demonstrate that TOMI significantly outperforms baseline methods in musical structural coherence and creative expression quality. A user study further confirms its effectiveness in supporting complete multi-track song generation and efficient human-AI co-creation within authentic production workflows.
📝 Abstract
Hierarchical planning is a powerful approach to model long sequences structurally. Aside from considering hierarchies in the temporal structure of music, this paper explores an even more important aspect: concept hierarchy, which involves generating music ideas, transforming them, and ultimately organizing them--across musical time and space--into a complete composition. To this end, we introduce TOMI (Transforming and Organizing Music Ideas) as a novel approach in deep music generation and develop a TOMI-based model via instruction-tuned foundation LLM. Formally, we represent a multi-track composition process via a sparse, four-dimensional space characterized by clips (short audio or MIDI segments), sections (temporal positions), tracks (instrument layers), and transformations (elaboration methods). Our model is capable of generating multi-track electronic music with full-song structure, and we further integrate the TOMI-based model with the REAPER digital audio workstation, enabling interactive human-AI co-creation. Experimental results demonstrate that our approach produces higher-quality electronic music with stronger structural coherence compared to baselines.