MusicBrainz Picard
Tags a music library automatically by audio fingerprint
Description
A few thousand tracks on disk, half of them tagged "track01" by "Unknown Artist", no cover art, and a player that sorts them into nonsense. Fixing that by hand — looking up release years and track numbers one file at a time — does not finish one album in an afternoon.
Picard inverts the problem: it ignores the filename and listens to the audio. Each file gets an acoustic fingerprint, matched against the MusicBrainz open music database of tens of millions of releases, and artist, album, track number, release year and cover art are written back in one pass. Wrong tags and garbled names do not affect recognition.
It also understands albums, clustering loose files into releases and matching them as a set, which is far more accurate than guessing track by track. Afterwards it renames and files everything by your own script — Artist/Year - Album/Track - Title, for instance. MP3, FLAC, AAC, Ogg, WMA and more, with plugins for lyrics, ratings and Beets interoperability. Free, open source, cross-platform.
Acoustic fingerprinting: AcoustID fingerprints matched against MusicBrainz, independent of filenames and existing tags.
Album-level matching: Loose tracks are clustered into releases and matched together, so track and disc numbers line up.
Cover art: Pulls artwork from the Cover Art Archive and embeds it, so players and phones display it correctly.
Scripted renaming: Define naming and folder structure in a script and have the library filed accordingly as it is tagged.
Broad format support: Reads and writes tags for MP3, FLAC, AAC, Ogg Vorbis, WMA and APE, so mixed libraries are handled uniformly.
Plugins: An official plugin catalogue adds lyrics fetching, rating sync and interoperability with tools such as Beets.
Picard inverts the problem: it ignores the filename and listens to the audio. Each file gets an acoustic fingerprint, matched against the MusicBrainz open music database of tens of millions of releases, and artist, album, track number, release year and cover art are written back in one pass. Wrong tags and garbled names do not affect recognition.
It also understands albums, clustering loose files into releases and matching them as a set, which is far more accurate than guessing track by track. Afterwards it renames and files everything by your own script — Artist/Year - Album/Track - Title, for instance. MP3, FLAC, AAC, Ogg, WMA and more, with plugins for lyrics, ratings and Beets interoperability. Free, open source, cross-platform.
Features
Acoustic fingerprinting: AcoustID fingerprints matched against MusicBrainz, independent of filenames and existing tags.
Album-level matching: Loose tracks are clustered into releases and matched together, so track and disc numbers line up.
Cover art: Pulls artwork from the Cover Art Archive and embeds it, so players and phones display it correctly.
Scripted renaming: Define naming and folder structure in a script and have the library filed accordingly as it is tagged.
Broad format support: Reads and writes tags for MP3, FLAC, AAC, Ogg Vorbis, WMA and APE, so mixed libraries are handled uniformly.
Plugins: An official plugin catalogue adds lyrics fetching, rating sync and interoperability with tools such as Beets.
