song-identification

AudioFingerprint is a production-ready, local audio fingerprinting and song identification system inspired by Shazam and Google Sound Search. It uses spectral peak extraction and combinatorial hashing to identify songs from short audio clips in milliseconds, with a clean Python + Flask architecture suitable for real-world deployments.

Song identification combining landmark audio fingerprinting with CNN/AST/MERT embeddings (contrastive InfoNCE), benchmarked on Jamendo with strong noise robustness.

TrackRadar is a music recognition bot that uses the Twitter API to identify songs from video content. Enhance your music discovery experience on Twitter with TrackRadar.

Ambient music identification for the Even Realities G2

Shazam-inspired audio fingerprinting engine for real-time music recognition.

Agent Skills that turn "what song is this?" into an answer, and that answer into a beatmatched set list. One command installs into Claude Code, Codex, Cursor, Gemini CLI and a dozen more.

Your media assistant in Telegram: download video & music from 200+ platforms (YouTube, TikTok no-watermark, Instagram…), find a song from a video or by humming, edit media — 20+ tools, AI subtitles, audio effects

MCP server for music recognition — identify any song from a link or an audio file, then get its BPM, musical key, Camelot code and harmonically compatible tracks. Works in Claude, Cursor, Windsurf and Zed. No API key.

Music Identifier App built with ShazamKit and SwiftUI, enabling users to recognize and discover songs seamlessly.

Nirvana is a music identifier extension designed to help users quickly identify songs playing in the browser.

Zham app

Identify any song from a link or an audio file, then read its BPM, musical key and Camelot code — from your terminal or your code. Node.js and Python clients, zero runtime dependencies, no API key.

Shazam is Apple's music recognition service that identifies songs from audio fingerprints. The Shazam API provides song recognition, music charts, and artist and track metadata retrieval. Originally launched in 2002 and acquired by Apple in 2018, Shazam processes over 1 billion song identifications per month.