the quest for musical genres: do the experts and the wisdom of crowds agree?

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This paper presents some findings around musical genres. The main goal is to analyse whether there is any agreement between a group of experts and a community, when defining a set of genres and their relationships. For this purpose, three different experiments are conducted using two datasets: the MP3.com expert taxonomy, and last.fm tags at artist level. The experimental results show a clear agreement for some components of the taxonomy (Blues, HipHop), whilst in other cases (e.g. Rock) there is no correlations. Interestingly enough, the same results are found in the MIREX2007 results for audio genre classification task. Thus, showing the fact that a musical genre could have a multi–faceted definition; using expert based classifications, dynamic associations derived from the community driven annotations, and content–based analysis would improve genre classification, as well as other relevant MIR tasks such as music similarity or music recommendation.

TRANSCRIPT

ISMIR / Philadelphia, US // September, 18th 2008

The Quest for Musical Genres:

Do the Experts and the Wisdom of Crowds Agree?

Mohamed Sordo, Òscar Celma, Martin Blech, Enric Guaus(Music Technology Group ~ UPF)

ISMIR / Philadelphia, US // September, 18th 2008 // òscar celma // MTG / UPF

motivation

taxonomy (controlled vocabulary)

ISMIR / Philadelphia, US // September, 18th 2008 // òscar celma // MTG / UPF

motivation

taxonomy (controlled vocabulary)

folksonomy (free text)

ISMIR / Philadelphia, US // September, 18th 2008 // òscar celma // MTG / UPF

motivation

taxonomy (controlled vocabulary)

VS. folksonomy (free text)

ISMIR / Philadelphia, US // September, 18th 2008 // òscar celma // MTG / UPF

expert-based

• taxonomy Mp3.com 2005

ISMIR / Philadelphia, US // September, 18th 2008 // òscar celma // MTG / UPF

expert-based

• taxonomy 13 seed genres (components) 7 levels 711 genres

Rock Hip-Hop

ISMIR / Philadelphia, US // September, 18th 2008 // òscar celma // MTG / UPF

community-based

• folksonomy last.fm

ISMIR / Philadelphia, US // September, 18th 2008 // òscar celma // MTG / UPF

community-based

• folksonomy last.fm ~137K artists ~90K tags (after cleaning)

ISMIR / Philadelphia, US // September, 18th 2008 // òscar celma // MTG / UPF

outline

1) Mapping tags to genres

2) Computing similarity among genres

3) Agreement between experts and wisdom of crowds

4) Reconstructing the taxonomy from the folksonomy

ISMIR / Philadelphia, US // September, 18th 2008 // òscar celma // MTG / UPF

outline

1) Mapping tags to genres

2) Computing similarity among genres

3) Agreement between experts and wisdom of crowds

4) Reconstructing the taxonomy from the folksonomy

ISMIR / Philadelphia, US // September, 18th 2008 // òscar celma // MTG / UPF

1) mapping tags to genres

ISMIR / Philadelphia, US // September, 18th 2008 // òscar celma // MTG / UPF

1) mapping tags to genres

• folksonomy ~ taxonomyJade (artist tags):

90s, illinois, new jack swing, rnb, r and b,

urban, ...

ISMIR / Philadelphia, US // September, 18th 2008 // òscar celma // MTG / UPF

1) mapping tags to genres

• folksonomy ~ taxonomyJade (artist tags):

90s, illinois, new jack swing, rnb, r and b,

urban, ...

ISMIR / Philadelphia, US // September, 18th 2008 // òscar celma // MTG / UPF

1) mapping tags to genres

• folksonomy ~ taxonomyJade (artist tags):

90s, illinois, new jack swing, rnb, r and b,

urban, ...

ISMIR / Philadelphia, US // September, 18th 2008 // òscar celma // MTG / UPF

1) mapping tags to genres

• folksonomy ~ taxonomyJade (artist tags):

R&B, New-Jack-Swing, Urban

ISMIR / Philadelphia, US // September, 18th 2008 // òscar celma // MTG / UPF

1) mapping tags to genres

• folksonomy ~ taxonomyJade (artist tags):

R&B, New-Jack-Swing, Urban

(39% tags matched

with MP3.com genres)

ISMIR / Philadelphia, US // September, 18th 2008 // òscar celma // MTG / UPF

outline

1) Mapping tags to genres

2) Computing similarity among genres

3) Agreement between experts and wisdom of crowds

4) Reconstructing the taxonomy from the folksonomy

ISMIR / Philadelphia, US // September, 18th 2008 // òscar celma // MTG / UPF

2) computing similarity among genres

• Taxonomy distance(Doo-Woop, Urban) = 3

Penalty when crossing components distance(Urban, Rock-Pop) = 7

ISMIR / Philadelphia, US // September, 18th 2008 // òscar celma // MTG / UPF

2) computing similarity among genres

• Folksonomy LSA (SVD), 50 dim.

Cosine similarity sim(Urban, Doo-Wop) = 0.868 sim(Urban, Pop-Rock) = -0.145

ISMIR / Philadelphia, US // September, 18th 2008 // òscar celma // MTG / UPF

outline

1) Mapping tags to genres

2) Computing similarity among genres

3) Agreement between experts and wisdom of crowds

4) Reconstructing the taxonomy from the folksonomy

ISMIR / Philadelphia, US // September, 18th 2008 // òscar celma // MTG / UPF

agreement experts ~ wisdom of crowds

• 1) Separate (taxonomy) genre components using (folksonomy) genre sim. intra-component similarity inter-component similarity

• 2) Correlation between (taxonomy) genre path distance and (folksonomy) genre sim. DistanceTAXONOMY(g1, g2) ~???~ SimFOLKSONOMY(g1, g2)

ISMIR / Philadelphia, US // September, 18th 2008 // òscar celma // MTG / UPF

agreement experts ~ wisdom of crowds

• 1) intra-component similarity, using LSA

ISMIR / Philadelphia, US // September, 18th 2008 // òscar celma // MTG / UPF

agreement experts ~ wisdom of crowds

• 1) intra-component similarity, using LSA

ISMIR / Philadelphia, US // September, 18th 2008 // òscar celma // MTG / UPF

agreement experts ~ wisdom of crowds

• 1) intra-component similarity, using LSA

Alternative-Rap

Dirty-Rap

West-Coast

Hip-hop

Bass-Music

ISMIR / Philadelphia, US // September, 18th 2008 // òscar celma // MTG / UPF

agreement experts ~ wisdom of crowds

• 1) intra-component similarity, using LSA

Blu

es

Hip

-hop

Rock

/Pop

Ele

ctro

nic

ISMIR / Philadelphia, US // September, 18th 2008 // òscar celma // MTG / UPF

agreement experts ~ wisdom of crowds

• 1) inter-component similarity centroid for each component

ISMIR / Philadelphia, US // September, 18th 2008 // òscar celma // MTG / UPF

agreement experts ~ wisdom of crowds

• 1) inter-component similarity Clearly distinguishable from the rest

Hip-hop, Blues, Jazz

Relationships found Country ~ Bluegrass (~ Folk) R&B-Soul ~ Gospel/Spiritual Electronic/Dance ~ Vocal/Easy-Listening New-Age ~ World/Reggae (!)

ISMIR / Philadelphia, US // September, 18th 2008 // òscar celma // MTG / UPF

agreement experts ~ wisdom of crowds

• 2) taxonomy genre distance vs. folksonomy genre sim.

West-Coast

Calypso

ISMIR / Philadelphia, US // September, 18th 2008 // òscar celma // MTG / UPF

agreement experts ~ wisdom of crowds

• 2) taxonomy genre distance vs. folksonomy genre sim. DistanceTAXONOMY(West-Coast, Calypso) = 8

West-Coast

Calypso

ISMIR / Philadelphia, US // September, 18th 2008 // òscar celma // MTG / UPF

agreement experts ~ wisdom of crowds

• 2) taxonomy genre distance vs. folksonomy genre sim. DistanceTAXONOMY(West-Coast, Calypso) = 7 SimFOLKSONOMY(West-Coast, Calypso) = 0.04

West-Coast

Calypso

ISMIR / Philadelphia, US // September, 18th 2008 // òscar celma // MTG / UPF

agreement experts ~ wisdom of crowds

• 2) taxonomy genre distance vs. folksonomy genre sim.

ISMIR / Philadelphia, US // September, 18th 2008 // òscar celma // MTG / UPF

outline

1) Mapping tags to genres

2) Computing similarity among genres

3) Agreement between experts and wisdom of crowds

4) Reconstructing the taxonomy from the folksonomy

ISMIR / Philadelphia, US // September, 18th 2008 // òscar celma // MTG / UPF

reconstruct taxonomy from folksonomy

• Select closest parent, using folk. genre sim. Get genres at level n

ISMIR / Philadelphia, US // September, 18th 2008 // òscar celma // MTG / UPF

reconstruct taxonomy from folksonomy

• Select closest parent, using folk. genre sim. For each genre at level n

ISMIR / Philadelphia, US // September, 18th 2008 // òscar celma // MTG / UPF

reconstruct taxonomy from folksonomy

• Select closest parent, using folk. genre sim. Get all nodes at level n-1 (possible parents)

ISMIR / Philadelphia, US // September, 18th 2008 // òscar celma // MTG / UPF

reconstruct taxonomy from folksonomy

• Select closest parent, using folk. genre sim. Compute cosine LSA similarity

ISMIR / Philadelphia, US // September, 18th 2008 // òscar celma // MTG / UPF

reconstruct taxonomy from folksonomy

• Select closest parent, using folk. genre sim. Assign closest parent

ISMIR / Philadelphia, US // September, 18th 2008 // òscar celma // MTG / UPF

reconstruct taxonomy from folksonomy

• Select closest parent, using folk. genre sim. Compare with taxonomy parent

ISMIR / Philadelphia, US // September, 18th 2008 // òscar celma // MTG / UPF

reconstruct taxonomy from folksonomy

• Results

ISMIR / Philadelphia, US // September, 18th 2008 // òscar celma // MTG / UPF

reconstruct taxonomy from folksonomy

• Results

ISMIR / Philadelphia, US // September, 18th 2008 // òscar celma // MTG / UPF

reconstruct taxonomy from folksonomy

• Results

ISMIR / Philadelphia, US // September, 18th 2008 // òscar celma // MTG / UPF

...and also!

• MIREX 2007 results (Team: IMIRSEL-M2K SVM)

RAPHIPHOP 84.05%BLUES 77.68%EDANCE 77.68%JAZZ 72.53%COUNTRY 71.37%ROCKROLL 69.53%BAROQUE 65.81%METAL 61.11%ROMANTIC 52.79%CLASSICAL 33.33%

ISMIR / Philadelphia, US // September, 18th 2008 // òscar celma // MTG / UPF

conclusions

• Consensus in some genres expert, community, and audio

• Discovery in terms of taxonomy/folksonomy coarse / fine grained static / dynamic

• Taxonomy adapts according to the folksonomy

• Do we need experts?

• Are some (wisdom-of-crowds) shepherds more experts than “THE” experts?

ISMIR / Philadelphia, US // September, 18th 2008 // òscar celma // MTG / UPF

future work

• Use more taxonomies and folksonomies

• Agreement measures

Uncovering affinity of artists to multiple genres from social behaviour data (Claudio Baccigalupo, Justin Donaldson, Enric Plaza)

ISMIR / Philadelphia, US // September, 18th 2008

THANKS!!!

Mohamed Sordo, Òscar Celma, Martin Blech, Enric Guaus(Music Technology Group ~ UPF)

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