M6(GPT)3: Generating Multitrack Modifiable Multi-Minute MIDI Music from Text using Genetic algorithms, Probabilistic methods and GPT Models in any Progression and Time Signature
Jakub Po\'cwiardowski, Mateusz Modrzejewski, Marek S. Tatara

TL;DR
This paper presents M6(GPT)3, a system that generates complex, multi-minute MIDI compositions from natural language prompts using GPT models, genetic algorithms, and probabilistic methods, enabling flexible musical structures and styles.
Contribution
The work introduces a novel hybrid system combining GPT, genetic algorithms, and probabilistic methods for structured, multi-minute MIDI music generation from natural language descriptions.
Findings
Outperforms baseline methods on key musical metrics
Generates music with complex structures and emotional expressiveness
Effective in producing diverse styles and time signatures
Abstract
This work introduces the M6(GPT)3 composer system, capable of generating complete, multi-minute musical compositions with complex structures in any time signature, in the MIDI domain from input descriptions in natural language. The system utilizes an autoregressive transformer language model to map natural language prompts to composition parameters in JSON format. The defined structure includes time signature, scales, chord progressions, and valence-arousal values, from which accompaniment, melody, bass, motif, and percussion tracks are created. We propose a genetic algorithm for the generation of melodic elements. The algorithm incorporates mutations with musical significance and a fitness function based on normal distribution and predefined musical feature values. The values adaptively evolve, influenced by emotional parameters and distinct playing styles. The system for generating…
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Taxonomy
TopicsMusic and Audio Processing · Music Technology and Sound Studies · Speech and Audio Processing
