music-identification

An open-source Shazam client for identifying music on your PC. For when your phone's microphone just doesn't cut it.

TuneSpy is a Python application that allows users to load audio files, generate spectrograms, extract MFCC features, and compare the loaded audio with a preprocessed database of songs to find the most similar match.

Shazam-style audio recognition system in Python using spectral peak hashing and time-offset matching. Ingest songs from YouTube, fingerprint them, and identify them from short microphone recordings.

POLARIS: training-free audio fingerprinting with saliency-based landmarks, Delaunay triplets, and asymmetric query expansion.

Code for the paper "Predicting Artificial Neural Network Representations to Learn Recognition Model for Music Identification from Brain Recordings".

🎵 Identify songs by recording clips using Python-driven audio fingerprinting with spectral analysis and peak-based hashing.

Fingerprint-based music and vocals identification app that generates spectrograms, extracts features, applies perceptual hashing, and finds the most similar songs based on fingerprint matching.

Finished: A web app to identify Quebec and Irish trad tunes.

Backend music identification service using deterministic acoustic landmark fingerprints, Go, PostgreSQL, Valkey, S3-compatible storage, and FFmpeg.