Automated Music Composition System Using Linguistic Descriptors
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Solution Overview
Problem
Current music composition systems fail to provide non-musicians with the ability to automatically create unique, professional-quality music suitable for various media products without requiring music theory knowledge, and they are limited by licensing restrictions, inflexible delivery options, and inability to learn and adapt to user preferences.
Innovation Solution
An automated music composition and generation system that uses linguistic and graphical icon-based musical experience descriptors to create music, allowing users to input emotions and artistic concepts, with a graphical user interface for intuitive music creation, and the ability to learn and evolve over time based on user interactions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If automated music composition systems use traditional music theory-based interfaces, then music composition quality can be maintained, but accessibility to non-musicians deteriorates
Solution Approach 1:
The patent introduces an intermediary layer between the user and the music composition engine. Instead of requiring users to directly manipulate music theory parameters, the system uses natural language processing and conceptual descriptors (emotions, styles, moods) as intermediaries that automatically translate into professional music composition parameters. This mediator layer enables non-musicians to create music without theoretical knowledge while maintaining composition quality.
Solution Approach 2:
The system replaces the mechanical system of music theory education and manual parameter adjustment with an automated artificial intelligence composition engine. The AI engine handles the complex music theory transformations automatically, substituting the need for users to learn and manually apply music theory rules. This substitution maintains professional-quality output while eliminating the complexity barrier for non-musicians.
2Adaptability or versatility
If automated music composition systems provide extensive customization options, then user control over music qualities improves, but system complexity increases
Solution Approach 1:
The patent segments the music composition control into distinct, manageable dimensions such as emotion/mood, style/genre, instrumentation, tempo, and energy qualities. Each dimension can be independently controlled through simple descriptors, allowing users to customize music qualities without being overwhelmed by a monolithic complex interface. The segmentation enables granular control while maintaining interface simplicity.
Solution Approach 2:
The system dynamically adjusts the level of automation and user control based on user preferences and project requirements. Users can choose to provide detailed descriptors for fine-grained control or use minimal descriptors for fully automated composition. The system adapts its complexity level to match the user's needs, providing extensive customization capabilities when required while maintaining simplicity when sufficient control is achieved with fewer parameters.
3Productivity
If automated music composition systems generate music quickly, then productivity increases, but ability to create unique professional-quality music deteriorates
Solution Approach 1:
The patent implements feedback loops where the AI composition engine continuously refines generated music based on quality assessments and user preferences. The system generates initial compositions rapidly, then iteratively improves them by analyzing emotional accuracy, stylistic consistency, and musical coherence. This feedback mechanism enables the system to maintain high productivity while achieving professional-quality unique music through automated refinement cycles.
Solution Approach 2:
The system combines multiple AI specialization modules (emotion recognition, style analysis, instrumentation expertise, harmonic theory) into a composite composition engine. Each module contributes specific expertise to the music generation process, and their integrated output produces unique professional-quality music. This composite approach maintains rapid generation speeds while ensuring high quality through the collective intelligence of specialized subsystems working together.
4Ease of operation
If automated music composition systems use licensing restrictions, then composer rights are protected, but ease of use for content creators deteriorates
Solution Approach 1:
The patent enables the system to automatically handle licensing and rights management without requiring manual intervention from users. The AI composition engine generates music with embedded licensing information and automatically manages rights clearance, allowing content creators to incorporate music seamlessly. This self-service approach protects composer rights through automated compliance mechanisms while maintaining ease of use by eliminating manual licensing procedures from the user workflow.
Data Source
AI summary
An automated music composition and generation system and process for producing one or more pieces of digital music, by providing a set of musical energy (ME) quality control parameters to an automated music composition and generation engine, applying certain of the selected musical energy quality control parameters as markers to specific spots along the timeline of a selected media object or event marker by the system user during a scoring process, and providing the selected set of musical energy quality control parameters to drive the automated music composition and generation engine to automatically compose and generate one or more pieces of digital music with control over the specified qualities of musical energy embodied in and expressed by the piece of digital music to composed and generated by the automated music composition and generation engine.