Online music metadata database
MusicBrainz
is a
MetaBrainz
project that aims to create a collaborative music database that is similar to the
freedb
project. MusicBrainz was founded in response to the restrictions placed on the
Compact Disc Database
(CDDB), a database for software applications to look up audio
CD
information on the Internet. MusicBrainz has expanded its goals to reach beyond a CD
metadata
(this is information about the performers, artists, songwriters, etc.) storehouse to become a structured online database for music.
[3]
[4]
MusicBrainz captures information about artists, their recorded works, and the relationships between them. Recorded works entries capture at a minimum the album title, track titles, and the length of each track. These entries are maintained by volunteer editors who follow community written style guidelines. Recorded works can also store information about the release date and country, the CD ID,
cover art
,
acoustic fingerprint
, free-form annotation text and other metadata. As of October 2023
[update]
, MusicBrainz contains information on roughly 2.2 million artists, 3.9 million releases, and 30.4 million recordings.
[5]
End-users can use software that communicates with MusicBrainz to add
metadata tags
to their digital media files, such as
ALAC
,
FLAC
,
MP3
,
Ogg Vorbis
or
AAC
.
Cover Art Archive
[
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]
MusicBrainz allows contributors to upload cover art images of releases to the database; these images are hosted by Cover Art Archive (CAA), a joint project between
Internet Archive
and MusicBrainz started in 2012. Internet Archive provides the bandwidth, storage and legal protection for hosting the images, while MusicBrainz stores metadata and provides public access through the Web and via an
API
for third parties to use. As with other contributions, the MusicBrainz community is in charge of maintaining and reviewing the data.
[6]
Until May 16, 2022,
[7]
cover art was also provided for items on sale at
Amazon.com
and some other online resources, but CAA is now preferred, because it gives the community more control and flexibility for managing the images. As of October 2023
[update]
, over 4.6 million images exist in the archive.
[8]
Fingerprinting
[
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]
Besides collecting metadata about music, MusicBrainz also allows looking up recordings by their
acoustic fingerprint
. A separate application, such as MusicBrainz Picard, is used to do this.
Proprietary services
[
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]
In 2000, MusicBrainz started using
Relatable's
patented TRM (a
recursive acronym
for TRM Recognizes Music) for acoustic fingerprint matching. This feature attracted many users and allowed the database to grow quickly. However, by 2005 TRM was showing scalability issues as the number of tracks in the database had reached the millions. This issue was resolved in May 2006 when MusicBrainz partnered with MusicIP (now
AmpliFIND
), replacing TRM with MusicDNS.
[9]
TRMs were phased out and replaced by MusicDNS in November 2008.
In October 2009 MusicIP was acquired by
AmpliFIND
.
[10]
Sometime after the acquisition, the MusicDNS service began having intermittent problems.
[
citation needed
]
AcoustID and Chromaprint
[
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]
Since the future of the free identification service was uncertain, a replacement for it was sought. The Chromaprint acoustic fingerprinting algorithm, the basis for
AcoustID
identification service, was started in February 2010 by a long-time MusicBrainz contributor Luka? Lalinsky.
[11]
While AcoustID and Chromaprint are not officially MusicBrainz projects, they are closely tied with each other and both are open source. Chromaprint works by analyzing the first two minutes of a track, detecting the strength in each of 12
pitch classes
, storing these eight times per second. Additional post-processing is then applied to compress this fingerprint while retaining patterns.
[12]
The AcoustID search server then searches from the database of fingerprints by similarity and returns the AcoustID identifier along with MusicBrainz recording identifiers, if known.
Licensing
[
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]
Since 2003,
[13]
MusicBrainz's core data (artists, recordings, releases, and so on) are in the
public domain
, and additional content, including moderation data (essentially every
original content
contributed by users and its elaborations), is placed under the Creative Commons
CC BY-NC-SA
-2.0 license.
[14]
The
relational database management system
is
PostgreSQL
. The server software is covered by the
GNU General Public License
.
The MusicBrainz client
software library
,
libmusicbrainz
, is licensed under the
GNU Lesser General Public License
, which allows use of the code by proprietary software products.
In December 2004, the MusicBrainz project was turned over to the
MetaBrainz Foundation
, a
non-profit
group, by its creator Robert Kaye.
[15]
On 20 January 2006, the first commercial venture to use MusicBrainz data was the
Barcelona
, Spain-based
Linkara
in their "Linkara Musica" service.
[16]
On 28 June 2007,
BBC
announced that it had licensed MusicBrainz's live data feed to augment their music web pages. The
BBC online music editors
would also join the MusicBrainz community to contribute their knowledge to the database.
[17]
On 28 July 2008, the beta of the new BBC Music site was launched, which publishes a page for each MusicBrainz artist.
[18]
[19]
MusicBrainz Picard
[
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]
MusicBrainz Picard is a
free and open-source
software application
for identifying,
tagging
, and organising
digital audio
recordings.
[20]
Picard identifies
audio files
and
compact discs
by comparing either their
metadata
or their
acoustic fingerprints
with records in the database.
[20]
Audio file metadata (or "tags") are a means for storing information about a recording in the file. When Picard identifies an
audio file
, it can add new information to it, such as the recording artist, the album title, the
record label
, and the date of release.
[21]
ListenBrainz
[
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]
ListenBrainz
is a
free and open source
project that aims to
crowdsource
listening data from digital music and release it under an
open license
.
[22]
It is a
MetaBrainz Foundation
project tied to MusicBrainz. It aims to re-implement Last.fm features that were lost following that platform's acquisition by CBS.
[23]
[24]
ListenBrainz takes submissions from media players and services such as
Music Player Daemon
,
Spotify
, and
Rhythmbox
in the form of listens. ListenBrainz can also import
Last.fm
and
Libre.fm
scrobbles in order to build listening history. As listens are released under an open license, ListenBrainz is useful for music research for industry and development purposes.
[25]
[26]
[27]
[28]
[29]
See also
[
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]
References
[
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]
- ^
"About"
.
MusicBrainz
. MetaBrainz.
Archived
from the original on 2015-05-08
. Retrieved
4 May
2015
.
- ^
"WHOIS Lookup"
.
ICANN
.
Archived
from the original on 2015-04-02
. Retrieved
23 March
2015
.
- ^
Highfield, Ashley. "
Keynote speech given at IEA Future Of Broadcasting Conference
Archived
2008-04-22 at the
Wayback Machine
",
BBC
Press Office, 2007-06-27. Retrieved on 2008-02-11.
- ^
Swartz, A.
(2002).
"MusicBrainz: A semantic Web service"
(PDF)
.
IEEE Intelligent Systems
.
17
: 76?77.
CiteSeerX
10.1.1.380.9338
.
doi
:
10.1109/5254.988466
.
Archived
(PDF)
from the original on 2015-04-03
. Retrieved
2015-08-28
.
- ^
"Database Statistics"
. MusicBrainz
. Retrieved
2023-10-10
.
- ^
Fabian Scherschel (10 October 2012).
"MusicBrainz and Internet Archive create cover art database"
. The H. Archived from
the original
on 7 December 2013.
- ^
"MetaBrainz Blog"
.
MetaBrainz Blog
. Retrieved
2022-08-04
.
- ^
"Database Statistics ? Cover Art"
. MusicBrainz
. Retrieved
2023-10-10
.
- ^
"New fingerprinting technology available now!"
(Press release). MusicBrainz community blog. 2006-03-12.
Archived
from the original on 2008-08-07
. Retrieved
2006-08-03
.
- ^
AmpliFIND Music Services: News
Archived
2013-09-21 at the
Wayback Machine
- ^
"Introducing Chromaprint ? Luka? Lalinsky"
. Oxygene.sk. 2010-07-24.
Archived
from the original on 2018-10-10
. Retrieved
2018-04-10
.
- ^
Jang, Dalwon; Yoo, Chang D; Lee, Sunil; Kim, Sungwoong; Kalker, Ton (2011-01-18).
"How does Chromaprint work? ? Luka? Lalinsky"
.
IEEE Transactions on Information Forensics and Security
.
4
(4): 995?1004.
doi
:
10.1109/TIFS.2009.2034452
.
S2CID
1502596
. Retrieved
2018-04-10
.
- ^
"MusicBrainz Licenses"
.
Archived
from the original on April 13, 2003
. Retrieved
2015-10-23
.
- ^
MusicBrainz License
as of 13-11-2010.
- ^
Kaye, Robert (2006-03-12).
"The MetaBrainz Foundation launches!"
(Press release). MusicBrainz community blog.
Archived
from the original on 2011-05-19
. Retrieved
2006-08-03
.
- ^
Kaye, Robert (2006-01-20).
"Introducing: Linkara Musica"
. MusicBrainz.
Archived
from the original on 2008-09-07
. Retrieved
2006-08-12
.
- ^
Kaye, Robert (2007-06-28).
"The BBC partners with MusicBrainz for Music Metadata"
. MusicBrainz.
Archived
from the original on 2007-06-30
. Retrieved
2007-07-10
.
- ^
Shorter, Matthew (2008-07-28).
"BBC Music Artist Pages Beta"
. BBC.
Archived
from the original on 2009-01-24
. Retrieved
2009-02-12
.
- ^
MusicBrainz and the BBC
Archived
2018-02-20 at the
Wayback Machine
as of 2013-03-16
- ^
a
b
Staff writer
(28 July 2011).
"MusicBrainz Picard at a Glance"
.
PC World
. IDG Consumer & SMB
. Retrieved
2015-09-14
.
- ^
Lightner, Rob (11 June 2012).
"Tag your music files correctly with MusicBrainz Picard"
.
CNET
. CBS Interactive
. Retrieved
2015-09-14
.
- ^
"ListenBrainz Goals"
.
ListenBrainz
. Retrieved
13 February
2021
.
- ^
O'Brien, Danny (3 June 2021).
"Organizing in the Public Interest: MusicBrainz"
.
Electronic Frontier Foundation
. Retrieved
9 December
2023
.
- ^
Vigliensoni, Gabriel; Fujinaga, Ichiro (23 October 2017).
"The Music Listening Histories Dataset"
.
Proceedings of the 18th International Society for Music Information Retrieval Conference
. Suzhou, China: ISMIR: 96?102.
doi
:
10.5281/zenodo.1417499
. Retrieved
17 February
2024
.
- ^
Singh, Param; Kamlesh, Dutta; Kaye, Robert; Garg, Suyash (2020).
"Music Listening History Dataset Curation and Distributed Music Recommendation Engines Using Collaborative Filtering"
.
Proceedings of ICETIT 2019
. Lecture Notes in Electrical Engineering. Vol. 605. pp. 623?632.
doi
:
10.1007/978-3-030-30577-2_55
.
ISBN
978-3-030-30576-5
.
S2CID
204103568
. Retrieved
13 February
2021
.
- ^
Yadav, Naina; Singh, Anil (December 2020). "Bi-directional Encoder Representation of Transformer model for Sequential Music Recommender System".
Forum for Information Retrieval Evaluation
. pp. 49?53.
doi
:
10.1145/3441501.3441503
.
ISBN
9781450389785
.
S2CID
231628582
. Retrieved
13 February
2021
.
- ^
Schedl, Markus; Knees, Peter; McFee, Brian; Bogdanov, Dmitry (22 November 2021).
"Music Recommendation Systems: Techniques, Use Cases, and Challenges"
.
Recommender Systems Handbook
. pp. 927?971.
doi
:
10.1007/978-1-0716-2197-4_24
.
ISBN
978-1-0716-2196-7
. Retrieved
9 December
2023
.
- ^
Pocaro, Lorenzo; Gomez, Emilia; Castillo, Carlos (12 July 2023).
"Assessing the Impact of Music Recommendation Diversity on Listeners: A Longitudinal Study"
.
ACM Transactions on Recommender Systems
.
arXiv
:
2212.00592
.
doi
:
10.1145/3608487
.
S2CID
254125611
. Retrieved
17 February
2024
.
- ^
Ray, Brian (6 December 2019).
"Build a useful ML Model in hours on GCP to Predict The Beatles' listeners"
.
Towards Data Science
. Towards Data Science Inc
. Retrieved
17 February
2024
.
Further reading
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External links
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]