Audio landmark fingerprinting as a Node Stream module
This module is a duplex stream (instance of stream.Transform) that converts a PCM audio signal into a series of audio fingerprints. It works with audio tracks as well as with unlimited audio streams, e.g. broadcast radio.
Credits
The acoustic fingerprinting technique used here is the landmark algorithm, as described in the Shazam 2003 paper.
The implementation in codegen_landmark.js
has been inspired by the MATLAB routine of D. Ellis "Robust Landmark-Based Audio Fingerprinting" (2009). One significant difference with Ellis' implementation is that this module can handle unlimited audio streams, e.g. radio, and not only finished audio tracks.
Note the existence of another good landmark fingerprinter in Python, dejavu.
Description
In a nutshell,
- a spectrogram is computed from the audio signal
- significant peaks are chosen in this time-frequency map. a latency of 250ms is used to determine if a peak is not followed by a bigger peak.
- fingerprints are computed by linking peaks with
dt
,f1
andf2
, ready to be inserted in a database or to be compared with other fingerprints.
In the background, about 12s of musical content is represented as a spectrogram (top frequency is about 10kHz). The blue marks are the chosen spectrogram peaks. Grey lines are peaks pairs that each lead to a fingerprint.
Given the same audio, this figure shows the same peaks and the internal forward threshold that prevent peaks from being too close in time and frequency. The backward threshold selection is not represented here.
Usage
npm install stream-audio-fingerprint
The algorithm is in codegen_landmark.js
.
A demo usage, using ffmpeg, is proposed in codegen_demo.js
.
var decoder = ;processstdin; var Codegen = ;var fingerprinter = ;decoderstdout; fingerprinter;
and then we pipe audio data, either a stream or a file
curl http://radiofg.impek.com/fg | nodejs codegen_demo.jscat awesome_music.mp3 | nodejs codegen_demo.js
License
See LICENSE file.