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.

1. 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)

2. ISMIR / Philadelphia, US // September, 18th 2008 // òscar celma // MTG / UPF
motivation
taxonomy (controlled vocabulary)

3. ISMIR / Philadelphia, US // September, 18th 2008 // òscar celma // MTG / UPF
motivation
taxonomy (controlled vocabulary)
folksonomy (free text)

4. ISMIR / Philadelphia, US // September, 18th 2008 // òscar celma // MTG / UPF
motivation
taxonomy (controlled vocabulary)
VS.
folksonomy (free text)

5. ISMIR / Philadelphia, US // September, 18th 2008 // òscar celma // MTG / UPF
expert-based
• taxonomy
 Mp3.com
 2005

6. ISMIR / Philadelphia, US // September, 18th 2008 // òscar celma // MTG / UPF
expert-based
• taxonomy
 13 seed genres (components)
 7 levels
 711 genres
Rock Hip-Hop

7. ISMIR / Philadelphia, US // September, 18th 2008 // òscar celma // MTG / UPF
community-based
• folksonomy
 last.fm


8. ISMIR / Philadelphia, US // September, 18th 2008 // òscar celma // MTG / UPF
community-based
• folksonomy
 last.fm
 ~137K artists
 ~90K tags (after cleaning)

9. 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

10. 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

11. ISMIR / Philadelphia, US // September, 18th 2008 // òscar celma // MTG / UPF
1) mapping tags to genres

12. ISMIR / Philadelphia, US // September, 18th 2008 // òscar celma // MTG / UPF
1) mapping tags to genres
• folksonomy ~ taxonomy
Jade (artist tags):
90s, illinois, new jack swing, rnb, r and b,
urban, ...

13. ISMIR / Philadelphia, US // September, 18th 2008 // òscar celma // MTG / UPF
1) mapping tags to genres
• folksonomy ~ taxonomy
Jade (artist tags):
90s, illinois, new jack swing, rnb, r and b,
urban, ...

14. ISMIR / Philadelphia, US // September, 18th 2008 // òscar celma // MTG / UPF
1) mapping tags to genres
• folksonomy ~ taxonomy
Jade (artist tags):
90s, illinois, new jack swing, rnb, r and b,
urban, ...

15. ISMIR / Philadelphia, US // September, 18th 2008 // òscar celma // MTG / UPF
1) mapping tags to genres
• folksonomy ~ taxonomy
Jade (artist tags):
R&B, New-Jack-Swing, Urban

16. ISMIR / Philadelphia, US // September, 18th 2008 // òscar celma // MTG / UPF
1) mapping tags to genres
• folksonomy ~ taxonomy
Jade (artist tags):
R&B, New-Jack-Swing, Urban
(39% tags matched
with MP3.com genres)

17. 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

18. 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

19. 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

20. 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

21. 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)

22. ISMIR / Philadelphia, US // September, 18th 2008 // òscar celma // MTG / UPF
agreement experts ~ wisdom of crowds
• 1) intra-component similarity, using LSA

23. ISMIR / Philadelphia, US // September, 18th 2008 // òscar celma // MTG / UPF
agreement experts ~ wisdom of crowds
• 1) intra-component similarity, using LSA

24. 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

25. ISMIR / Philadelphia, US // September, 18th 2008 // òscar celma // MTG / UPF
agreement experts ~ wisdom of crowds
• 1) intra-component similarity, using LSA
Blues
Hip-hop
Rock/Pop
Electronic

26. ISMIR / Philadelphia, US // September, 18th 2008 // òscar celma // MTG / UPF
agreement experts ~ wisdom of crowds
• 1) inter-component similarity
 centroid for each component

27. 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 (!)

28. 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

29. 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

30. 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

31. ISMIR / Philadelphia, US // September, 18th 2008 // òscar celma // MTG / UPF
agreement experts ~ wisdom of crowds
• 2) taxonomy genre distance vs. folksonomy
genre sim.

32. 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

33. 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

34. 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

35. 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)

36. 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

37. ISMIR / Philadelphia, US // September, 18th 2008 // òscar celma // MTG / UPF
reconstruct taxonomy from folksonomy
• Select closest parent, using folk. genre sim.
 Assign closest parent

38. 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

39. ISMIR / Philadelphia, US // September, 18th 2008 // òscar celma // MTG / UPF
reconstruct taxonomy from folksonomy
• Results

40. ISMIR / Philadelphia, US // September, 18th 2008 // òscar celma // MTG / UPF
reconstruct taxonomy from folksonomy
• Results

41. ISMIR / Philadelphia, US // September, 18th 2008 // òscar celma // MTG / UPF
reconstruct taxonomy from folksonomy
• Results

42. 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%

43. 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?

44. 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)

45. ISMIR / Philadelphia, US // September, 18th 2008
THANKS!!!
Mohamed Sordo, Òscar Celma, Martin Blech, Enric Guaus
(Music Technology Group ~ UPF)