Presented by Maria Pantelli Fifth British Library Labs (BL Labs) Symposium, Monday October 30, 2017 This Award recognises a project or activity which shows the development of new knowledge, research methods, or tools using the Library’s digital content.

1. A large-scale comparison of world music corpora
with computational tools
Maria Panteli, Emmanouil Benetos, Simon Dixon
Centre for Digital Music,
School of Electronic Engineering and Computer Science,
Queen Mary University of London
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2. motivation
• music has travelled beyond country borders
• but…is this true for all countries?
• can we find music examples that stand out from other musics in
the world?
1

3. challenges: corpus
• no single archive containing all the
music of the world
• combine music from two archives
• from ~70,000 recordings to ~8,000
geographically balanced
• World and Traditional Music subset
curated for the Digital Music Lab
project http://dml.city.ac.uk/
• contribution: large(st) world music
corpus for research
•
1 8 17 28 43 61 84 155 246 437
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4. challenges: metadata
• Country: Yugoslavia (former)
• Location: Singer’s home
• Language: Acholi (Labwor), Acholi (Nyakwai), Acholu, Acoli
• Year: 1965/10/01, 10-03-1978, 1980s, ca. 1987
• contribution: curated metadata
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5. data processing
pre-processing signal processing + machine learning data mining
Music
Speech Speech
Feature
learning Pooling
8-second frames
MFCC stats
Scale transform
Chroma stats
Pitch bihistogram
Melfrequency
Time
Pitchclass
Analysis
rhythm
timbre
melody
harmony
outlier
detection
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6. results: outlier recordings
90 − 100 %
80 − 90 %
70 − 80 %
60 − 70 %
50 − 60 %
40 − 50 %
30 − 40 %
20 − 30 %
10 − 20 %
0 − 10 %
NA
out of 137 countries,
Botswana is the country with
the most outlier recordings
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7. results: rhythm features
rhythmic outliers often
feature the use of
polyrhythms
90 − 100 %
80 − 90 %
70 − 80 %
60 − 70 %
50 − 60 %
40 − 50 %
30 − 40 %
20 − 30 %
10 − 20 %
0 − 10 %
NA
1

8. results: harmony features
harmonic outliers often
feature inharmonic
instruments (gong, bells)
90 − 100 %
80 − 90 %
70 − 80 %
60 − 70 %
50 − 60 %
40 − 50 %
30 − 40 %
20 − 30 %
10 − 20 %
0 − 10 %
NA
1

9. demo
mpanteli.github.io/music-outliers/demo/
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10. future directions
• expand the corpus
• improve computational models
• more corpus studies in world music

11. Thank you British Library Labs!
Maria Panteli*, Emmanouil Benetos, Simon Dixon
Queen Mary University of London
*m.panteli@qmul.ac.uk
mpanteli.github.io/music-outliers/demo/