AI Describe Music - Hear More. Create Better.

What Is It?

AI-Driven Audio Analysis Engine  
Describe Music is an artificial intelligence platform designed to decode the complex attributes of audio files within seconds. By leveraging deep neural networks, it transforms raw audio into structured metadata, solving core challenges for music professionals and enthusiasts alike.  

Key Capabilities  
• Genre Identification: Classifies both mainstream and niche styles (e.g., "Synthwave with 80s retro influences")  

• Mood Profiling: Detects emotional resonance through spectral analysis (e.g., "Energetic (85%), Nostalgic (72%)")  

• Technical Parameter Extraction:  

 ✓ BPM Detection: Tolerance range ±2 BPM  
 ✓ Key Recognition: Major/Minor modes with confidence scoring  
 ✓ Loudness Normalization: Measured in LUFS  

Unique Value Proposition  
• Obscure Track Compatibility: Effectively analyzes non-commercial/demo recordings  

• Zero Data Retention Policy: Files purged immediately post-analysis (audit trail available)  

How It Works

Technical Workflow  
1. Secure Upload:  
  • 256-bit SSL encrypted transfer  

  • File size cap: 50MB (≈5 min @ 320kbps MP3)  

2. AI Processing Pipeline:  
  • Stage 1: Mel-spectrogram conversion (96kHz sampling)  

  • Stage 2: Feature extraction via convolutional layers  

  • Stage 3: Temporal modeling through Transformer blocks  

Report Generation:  

  • Interactive web interface with waveform visualization  

  • Export options: HTML summary / JSON metadata  

Supported Formats  
Format Bit Depth Sample Rate
MP3 16-320kbps 44.1-48kHz
WAV 16/24-bit 44.1-192kHz
FLAC 16/24-bit 44.1-192kHz
AAC ≤256kbps 44.1-48kHz
3. Use Cases

Music Production Workflow  
Problem: Producers spend 15-20 hours/week manually tagging sample libraries.  

Solution: Batch analysis reduces tagging time by 80% with >90% consistency.  

Content Creation Optimization  
Scenario: Podcasters needing "suspenseful" background tracks for true-crime episodes.  

Implementation: Mood filter → "Dark/Anxious" → BPM range 60-80 → Instant match.  

Educational Applications  
Case: Music teachers demonstrating harmonic analysis of jazz standards.  

Value: Real-time key modulation graphs during classroom sessions.  

Some User Testimonials We have found

Verified Creator Feedback  
@FilmScoringPro:  

"The key detection accuracy saved my orchestral session - identified Debussy's whole-tone scale usage in my draft with 100% precision."  


@IndieGameDev:  

"Tagged 2,300 weapon SFX in 4 hours (previously 3-week task). The 'metallic resonance' parameter was crucial for VR audio design."  

Compatibility & Performance

Cross-Platform Accessibility  
Environment Requirements
Desktop Chrome 110+, Firefox 108+, Edge 109+
Mobile iOS Safari 16.4+, Android Chrome 112+
Bandwidth Min. 5 Mbps for upload