Mp25: Audio Fingerprinting and metadata correction with Python

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This document discusses using Python for audio fingerprinting and metadata correction of music files. It describes using multiple music metadata sources like MusicBrainz, Amazon, and Last.fm to get consistent metadata and identify tracks via fingerprinting when metadata is missing. The key steps are fingerprinting audio to identify tracks, using metadata from sources to fill in artist, album, genre and image tags, and writing this standardized metadata to music files. The goal is to make it easy for people to consistently name and tag their music collections.

Technology Entertainment & Humor

Audio ﬁngerprinting and metadata
correction with Python

Alastair Porter

November 21, 2011

Me

Background in Computer Science
Masters McGill Music Tech
Online
http://github.com/alastair (20/28 music; 11 in python)
http://twitter.com/alastairporter

Python as a go-to language

Quick for prototyping
Use the same code in a production release
Very handy for API access (thin wrapper around urllib2)

Music and Metadata

The problem:
People are really bad at naming music
Inconsistent over releases

The solution:
Crowdsourcing
Get info from as many trusted sources as possible
Make renaming take no effort

albumidentify

http://github.com/albumidentify/albumidentify

Identiﬁcation strategy

If there’s a CD TOC, use that (musicbrainz lookup)
If no match, use audio ﬁngerprinting
If no match, do a text lookup (artist/album)

Fingerprinting

Converts an audio signal to a short sequence of numbers
Smaller to compare than an entire ﬁle
Perceptual features rather than byte comparison (works
with different encodings)

Identiﬁcation strategy

Fingerprinting gives us a set of candidate tracks
A track could be on many albums (original release, best of,
mix album)
Keep a list of what tracks we have for each album
Once we ﬁll all the slots for an album, success!

Metadata strategy

Text information from Musicbrainz
Genre from last.fm
Image from Amazon (or folder.jpg)
Musicbrainz tells us where these are (don’t need to search)
Save in every ﬁle (Text is cheap)

Writing it all out

Custom MP3/ID3 writer
Ogg meta tags
FLAC meta tags
Name ﬁles
Artist/Artist - Year - Album/01 - Artist - Track
Replaygain!
Be a good citizen: Submit ﬁngerprints to musicbrainz

What’s next

New version of musicbrainz
New ﬁngerprinter
More metadata
More metadata

Thanks

More information:
MusicBrainz: http://musicbrainz.org
albumidentify:
http://github.com/albumidentify/albumidentify
More ﬁngerprinting: http://acoustid.org,
http://echoprint.me
Last.fm

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Mp25: Audio Fingerprinting and metadata correction with Python

1. Audio ﬁngerprinting and metadata correction with Python Alastair Porter November 21, 2011

2. Me Background in Computer Science Masters McGill Music Tech Online http://github.com/alastair (20/28 music; 11 in python) http://twitter.com/alastairporter

3. Python as a go-to language Quick for prototyping Use the same code in a production release Very handy for API access (thin wrapper around urllib2)

4. Music and Metadata

5. Music and Metadata The problem: People are really bad at naming music Inconsistent over releases The solution: Crowdsourcing Get info from as many trusted sources as possible Make renaming take no effort

6. MusicBrainz

7. Amazon

8. Amazon (Coverart)

9. Last.fm

10. Last.fm (Genre tags)

11. MusicBrainz

12. albumidentify http://github.com/albumidentify/albumidentify

13. MP3, FLAC, Ogg, CDs

14. Identiﬁcation strategy If there’s a CD TOC, use that (musicbrainz lookup) If no match, use audio ﬁngerprinting If no match, do a text lookup (artist/album)

15. Fingerprinting Converts an audio signal to a short sequence of numbers Smaller to compare than an entire ﬁle Perceptual features rather than byte comparison (works with different encodings)

16. Identiﬁcation strategy Fingerprinting gives us a set of candidate tracks A track could be on many albums (original release, best of, mix album) Keep a list of what tracks we have for each album Once we ﬁll all the slots for an album, success!

17. Metadata strategy Text information from Musicbrainz Genre from last.fm Image from Amazon (or folder.jpg) Musicbrainz tells us where these are (don’t need to search) Save in every ﬁle (Text is cheap)

18. Writing it all out Custom MP3/ID3 writer Ogg meta tags FLAC meta tags Name ﬁles Artist/Artist - Year - Album/01 - Artist - Track Replaygain! Be a good citizen: Submit ﬁngerprints to musicbrainz

19. What’s next New version of musicbrainz New ﬁngerprinter More metadata More metadata

20. Thanks More information: MusicBrainz: http://musicbrainz.org albumidentify: http://github.com/albumidentify/albumidentify More ﬁngerprinting: http://acoustid.org, http://echoprint.me Last.fm

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