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MusicBrainz has used several audio fingerprinting systems over its lifetime.

All of them (so far) work in essentially the same way based on ACR technology. It is generally a two-step process of submission and lookup. First, the raw audio is used to create a fingerprint, which is then submitted to a third-party server. This server analyzes the fingerprint, compares it to other fingerprints, and decides whether it is sufficiently different from known fingerprints as to issue a new ID.

Once this step is done, a fingerprint can be calculated for any file and this can be used to look up the corresponding ID.

This ID is associated with a given track (pre-NGS) or recording (post-NGS), and metadata can be gathered from there.


AcoustID is MusicBrainz’ third and most recent audio fingerprinting system. This was created by Lukáš Lalinský, and made public around January 2011.[1]

AcoustID support was implemented in Picard 0.16 released in October 2011.[2]

It has several immediate advantages:

  • It is open source.
  • It is actively developed, along with supporting software.
  • It gives the ability to visually compare music
  • AcoustID fingerprints have their duration recorded, making it easy to discard certain incorrect links between recordings and acoustIDs.

Older fingerprinting systems


TRM (TRM Recognizes Music) IDs were MusicBrainz’ first audio fingerprinting system. This system was created by Relatable, and added to MusicBrainz in 2000.[3]

This system was used in the original MusicBrainz tagger application. The client-side audio fingerprinting library was open source and integrated into libmusicbrainz.

This system worked reasonably well for finding duplicate music files on a local system, but had problems with collisions (different-sounding audio which got the same ID) and duplicates (same-sounding audio which has different IDs). The server was also incapable of handling the number of TRMs needed for MusicBrainz, and Relatable didn’t seem to be interested in supporting it further.[4]

TRM support was removed in November 2008[5].


PUIDs were MusicBrainz’ second audio fingerprinting system. This was initially operated by MusicIP (later AmpliFIND Music Services), and bought by Gracenote in June 2011. Gracenote is expected to discontinue the public service soon, and it already appears to be largely non-functional.

MusicBrainz started to use these IDs in March 2006[6] and they were implemented in Picard 0.7.0 released in July 2006.[7]

This system was better than TRM, but still had several major problems:

  • The fingerprint submission system is not open source, and as such could not be included in Picard. Only looking up existing fingerprints was possible in Picard, new fingerprints had to be created using either MusicIP Mixer or the command line genpuid (no longer available).
  • The fingerprinting process is slow, both on the client side and the server side
  • Over time, the operators have become less and less interested in running the server, to the point where today it is barely working, if it works at all.

PUIDs are also quite opaque, being nothing more than a unique number referencing a database outside of MusicBrainz’ control. If/when that database goes away, they become useless. See the patent application for details on the technology. The client-side audio fingerprinting library, libofa, is open-source.

PUID support was removed from the MusicBrainz server in October 2013.[8][9]

In June 2020 [10] all PUID edits were removed from the database.

Other audio fingerprinting systems

Open Source

  • The fingerprint in Kurt Rosenfeld's FDMF.
  • MusicURI, part of the Mpeg-7 Audio DB project.
  • AudioScout. Based on the pHash audio fingerprinting library, developed by the same authors. Uses the "Philips Robust Hashing" algorithm.
  • OpenFP.
  • Echoprint. Audio fingerprinting solution developed by the Echo Nest.
  • [defunct] libFooID. An audio fingerprinting library used by, and developed for foosic.
  • [defunct] Freetantrum. It seems to be a dead project (its home page was replaced with an advert for unrelated things in 2001), but it may be worth investigating and resurrecting the code they produced.
  • [defunct] jHears is an acoustic fingerprinting framework based on FutureProofFingerPrint design by Geoff Schmidt (formerly of Tuneprint). jHears is developed by Juha Heljoranta.

Partially Open-Source