Generative Music System Using Rule-Based Templates and AI
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Solution Overview
Problem
Current music generation software limits users to creating incomplete music works due to the complexity of music theory and the need for selecting individual pre-generated loops, making it impractical for most users to generate a complete, musically pleasing composition.
Innovation Solution
A rule-based generative music system utilizing AI technology and structured, customizable templates, organized in a three-phase process: input, data determination, and render phases, allowing users to select genres, audio collections, and templates to generate complete music works with AI-assisted audio loop selection and harmony presets.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If users select individual pre-generated loops to create music compositions, then users can create music without knowing music theory, but users can only generate incomplete music works
Solution Approach 1:
The music generation process is divided into distinct phases: input phase (collecting user preferences), data determination phase (AI processing and parameter determination), and render phase (generating audio output). This segmentation allows the system to handle complexity internally while keeping the user interface simple, enabling users to create complete music works without needing to understand music theory.
Solution Approach 2:
The system introduces an intermediary AI processing layer that translates simple user inputs (genre selection, mood preferences) into complex music composition decisions. This intermediary handles the sophisticated music theory requirements internally, allowing users to create complete music works without directly engaging with complex musical parameters.
2Manufacturing precision
If the music generation process provides detailed control over music parameters, then music quality can be improved, but the system becomes too complex for novice users
Solution Approach 1:
The system extracts and internalizes the complex music theory knowledge and composition rules within the AI model and predefined templates. Users only need to provide high-level preferences, while the system handles the detailed music parameter control automatically, maintaining both quality and simplicity.
Solution Approach 2:
The system dynamically adjusts music composition parameters based on user preferences and AI-determined values. By automatically managing parameter changes internally, the system maintains high music quality without requiring users to understand or control individual parameters, thus reducing operational complexity.
3Adaptability or versatility
If users manually assemble music compositions from individual loops, then customization is possible, but the process becomes impractical for complete music works
Solution Approach 1:
The system performs preliminary actions by pre-defining music templates, audio collections, and harmony presets that encapsulate complete music arrangements. Users can select from these pre-prepared elements and customize them at a high level, achieving both customization and complete music work generation without manual assembly of individual loops.
4Manufacturing precision
If the system provides comprehensive music theory knowledge and tools, then music quality improves, but accessibility to novice users decreases
Solution Approach 1:
The system provides self-service by automatically applying music theory rules, harmony principles, and composition techniques through its AI model and predefined templates. Users benefit from sophisticated music theory accuracy without needing to learn or apply these concepts themselves, maintaining both quality and accessibility.
Data Source
AI summary
According to a first embodiment, there is presented here a method of rule-based algorithmic generative music system. Templates are provided that contain all the information needed to build a music work, wherein this information combines the vast audio material stored in databases efficiently for selection, arrangement, and adaptation and in the end generation of the output music work.