4.3 KiB
MOTIF Project - Thursday Status Report
Project Overview
MOTIF is a procedural music synthesis system that extracts structural information from existing MIDI files and recreates them as original, real-time audio using Web Audio API. The core concept: "music as executable structure, not static audio."
Workflow
- User searches for a song by name
- System finds MIDI files from multiple sources (BitMidi, Dongrays)
- MIDI is parsed and analyzed for structural features (tempo, density, melodic patterns)
- Notes are mapped to synthesis "roles" (bass, drone, ostinato, texture, accents)
- Web Audio API generates procedural audio with similar "feel" but original sound
Current Status: Functional MVP
✅ Completed Features
Complete Search Pipeline
- Multi-source MIDI search with confidence scoring
- Real MIDI integration with fetching and parsing
- Graceful error handling and timeouts
Role-Based Synthesis Engine
- Intelligent mapping of MIDI tracks to synthesis layers
- Role-specific oscillator types and filtering
- Velocity-sensitive ADSR envelopes
- Polyphonic chord support
- Automatic looping and proper cleanup
Polished User Interface
- Search results table with confidence bars and quality analysis
- Dual player UI: Preview Original MIDI vs Generate Motif
- Real-time status updates and progress feedback
- "Try Next Result" workflow for easy A/B testing
Backend Infrastructure
- Express + TypeScript server
- CORS proxy with validation and SHA256 disk caching
- Multi-source search (BitMidi, Dongrays, synthetic fallback)
- Quality assessment with penalties for problematic content
📈 Recent Progress (Latest Commit)
Major UI/UX Improvements:
- Implemented search results table with metadata display
- Added MIDI preview player with basic oscillator mapping
- Built dual transport controls for comparison
- Integrated ParsedMIDIInfo with comprehensive track analysis
- Enhanced confidence scoring system with quality penalties
Technical Enhancements:
- Sophisticated role mapping with pitch range and density analysis
- Improved error handling across the pipeline
- Better synthesis scheduling with Web Audio lookahead
- Streamlined search-to-synthesis workflow
Current Problems & Limitations
🔴 Performance Issues
- ~70% search success rate (goal: >90%)
- ~30% musical similarity recognition (goal: >70%)
- HTML regex parsing is fragile (should use DOM parsing)
🟡 Feature Limitations
- Basic role mapping heuristics (lacks harmonic analysis)
- Simple synthesis timbres (basic oscillators only)
- Limited MIDI source coverage
- No user controls for synthesis parameters
🟠 Technical Debt
- Need more robust parsing for edge cases
- Search confidence scoring could be more sophisticated
- Some synthesis roles need refinement
Next Sprint Priorities
Phase 1: Core Stability (Next 1-2 weeks)
- Improve search success rate - better error handling, additional sources
- Enhance role mapping - add harmonic analysis, rhythm detection
- Polish synthesis - more interesting timbres, dynamic control
- Robust parsing - replace regex with proper DOM parsing
Phase 2: Musical Intelligence (2-4 weeks)
- Smarter scoring - melodic similarity, harmonic progression analysis
- Advanced synthesis - effects, modulation, realistic instruments
- User controls - synthesis parameter adjustment, role customization
- More MIDI sources - expand search coverage
Phase 3: Production Ready (1-2 months)
- Performance optimization - caching, preloading, worker threads
- Legal compliance - proper attribution, copyright handling
- User uploads - allow custom MIDI file analysis
- Production infrastructure - deployment, monitoring, scaling
Technical Architecture
Backend: Express + TypeScript with multi-source search, CORS proxy, and caching Frontend: TypeScript + Vite + Web Audio with real-time synthesis Key Components: MotifEngine, RoleMapper, SynthesisEngine, MIDIPlayer
Demo Status
✅ Ready to demonstrate - Full end-to-end pipeline functional
✅ User-friendly interface - Polished search and playback experience
✅ Comparative validation - Side-by-side original vs synthesis preview
The project successfully proves the core concept and is ready for user testing and iterative improvement.