Describe Music — AI Audio Analysis Tool
Describe Music is an AI-driven audio analysis platform that converts audio files into rich, structured music descriptions and metadata. It combines signal-processing and machine learning models to detect genre, mood, instruments, tempo (BPM), key, speech characteristics, and sound effects — and outputs SEO-friendly tags and exportable reports.
Key features
- Genre & mood detection: Automatic classification of music genre and emotional tone using trained audio classifiers.
- Instrument and event recognition: Identifies primary instruments and sound-events (nature, urban noise, effects) via audio tagging models.
- Voice & speech analysis: Speaker gender detection, emotion scoring, and clarity metrics for podcasts and voice recordings.
- Tempo & key extraction: BPM and musical key detection using signal analysis and pitch-tracking algorithms.
- Instant analysis & credits: Quick analysis UI with a credit-based trial (1 second = 1 credit), client-side uploads, and demo samples.
- Export & integration: Export results as JSON, CSV, or text reports and shareable links; API and developer-focused integrations available.
- Formats & limits: MP3 supported in the free quick-analyze flow; PRO supports WAV, FLAC, AAC, M4A, OGG, PCM and larger uploads.
- History & account features: Auto-save analysis history, search, and an export center for organizing outputs.
Target users & use cases
- Musicians & producers: Get objective instrument breakdowns, structure analysis, and key/BPM data to iterate on demos.
- Podcasters & YouTubers: Verify audio quality, tag music for show notes, and extract mood metadata for chapters and descriptions.
- Marketers & agencies: Ensure brand-safe music selection, generate ad copy from mood tags, and find licensed audio for campaigns.
- Game developers & sound designers: Bulk-tag sound libraries and speed up asset search with generated metadata.
- Developers: Use the API to integrate automatic audio tagging and SEO tag generation into applications or content workflows.
Technical notes
- Combines audio signal processing (spectral analysis, onset detection, pitch tracking) with supervised ML models for classification and tagging.
- Outputs structured metadata suitable for search, indexing, and programmatic workflows (JSON/CSV).
- Designed for low-latency client uploads and server-side analysis with credit accounting for usage-based billing.
Unique selling points
- Fast, demo-friendly quick analysis with clear trial credits.
- Comprehensive multi-domain analysis (music, voice, sound effects) in one tool.
- Built-in SEO tag generation and export formats to streamline publishing and content workflows.
