KU Leuven Music Multimedia Course

MULTIMEDIA COURSE:
MUSIC
Sten Govaerts

Saturday 26 February 2011

Katholieke
Universiteit Leuven


Leuven


...NOW LET’S GET TO
BUSINESS!


Without music life
would be a mistake. T

Friedrich Wilhelm Nietzsche


YET ANOTHER PROBLEM?
Bartender DJ Customers



what we do!


what we do! HAPPY!


business what we do! HAPPY!
is good

WHY LIKE THIS?


WHY LIKE THIS?

• how does an expert select his music?


WHY LIKE THIS?


• how does a bartender select his music?


WHY LIKE THIS?



• making the expert data accessible in a usable way for
a bartender


WHY LIKE THIS?



• making the expert data accessible in a usable way for
a bartender

A musical context is a musical description for situations based on
atmospheres and musical properties.


EXPERTS @ WORK
songs param. value matches


THE SCHEME


TROUBLE IN EXPERT LAND


LET’S CREATE A CONTEXT!


LET’S CREATE A CONTEXT!

subgenre: easy listening, pop café
popularity: 5, 6, 7
mood: relax, tasteful, stylish


context


context
subcontext A


context
subcontext A
songs with
subgenre(easy listening
OR pop café)


context
subcontext A
songs with
OR pop café)
+
songs with
mood(relax OR tasteful
OR stylish)


context
subcontext A
songs with
OR pop café)
+
songs with
OR stylish)
+
songs with
popularity(5 UNTIL 7)


context
subcontext A subcontext B
songs with
OR pop café)
+
songs with
OR stylish)
+
+
songs with


context
songs with songs with
subgenre(easy listening genre(pop)
OR pop café)
+
songs with
OR stylish)
+
+
songs with


context
OR pop café)
+
+
songs with
songs with
mood(intimate OR
OR stylish)
+ romantic
OR sensual)
+
songs with


context
OR pop café)
+
+
songs with
songs with
mood(intimate OR
OR stylish)
+ romantic
OR sensual)
+
+
popularity(5 UNTIL 7) popularity(6 UNTIL 7)


context
OR pop café)
+

75% 25%
+
songs with
songs with
mood(intimate OR
OR stylish)
+ romantic
OR sensual)
+
+
popularity(5 UNTIL 7) popularity(6 UNTIL 7)


WHAT’S UNDER THE HOOD?


HTTP://WWW.TUNIFY.COM


WHAT’S NEXT?...

• manually annotated metadata

•5 music experts at Aristo Music and
different consultants

• about 200,000 songs

• but, not enough...


THE LONG TAIL

http://en.wikipedia.org/wiki/Long_Tail

OTHER PROBLEMS...

• satisfyingthe music choice of all
customers

• retail and catering differ from you
and me!

• new markets

• react fast on emerging music trends

• adding the full Belgian library catalog


GENERATE THE METADATA

• from different sources:

• the audio signal
• web sources
• the Aristo database
• attention metadata

• using our metadata generation framework: SamgI


TWO TECHNIQUES

• Genre

• Country of Origin


GENRE...

http://techno.org/electronic-music-guide/
• our master thesis looked at different ways to generate genre...


GENRE


CLASSIFICATION WITH
SEARCH ENGINES
using co-occurrence


CLASSIFICATION WITH
SEARCH ENGINES
using co-occurrence

Artist + Genre + Schema


Rock: Jazz:

Blues: Pop:

Country: Metal:


Rock: Jazz:

0,013 0,013
Blues: Pop:

0,009 0,015
Country: Metal:

0,009 0,005


HOW TO EVALUATE THIS?

• run an experiment

• evaluate on 1995 artists and 9 genres.

• different search engines: Google,Yahoo! and Live! Search.

• over time: 8 times over a period of 36 days.


THE DATA SET
Blues Country Electronic
Folk Jazz Metal
Rap Reggae RnB


THE DATA SET
Blues Country Electronic
Folk Jazz Metal
Rap Reggae RnB
10% 9%
3%
2% 12%
13% 5%
4%

41%


MOTION CHART

• http://hmdb.cs.kuleuven.be/muzik/gapminder.html


MORE FINE-GRAINED...

• 18 artists

• more search engines: Google.co.uk/.fr/.be, uk/
fr.search.yahoo.com

• twice a day for 53 days

• 250,000 queries!


2 Pac Rap
Alan Lomax Folk
Art Pepper Jazz
Cradle of Filth Metal
David Parsons Electronic
Desmond Dekker Reggae
Downpour Metal
IceT Rap
Jerry Butler RnB
Joy Lynn White Country
Louisiana Red Blues
Lou Rawls RnB
LTJ Bukem Electronic
Peter Tosh Reggae
Pinetop Smith Jazz
Robert Johnson Blues
Roy Rogers Country
Steeleye Span Folk


MAIN SEARCH ENGINE
RESULTS


REGIONAL GOOGLES


WHAT TO USE?

• use Google when it’s stable else rely on Yahoo!

• when is it stable? test with a small set

• some artists get classiﬁed incorrectly on bad days

• compare the accuracy achieved with the test set to the
average.


DEMO METADATA
GENERATION

• http://ariadne.cs.kuleuven.be/samgi-service/


COUNTRY OF ORIGIN


MASHUPS


MASHUPS
• mashups in music: re-mixing multiple existing songs to
create a new one.


MASHUPS
create a new one.

•a mashup is an application that combines data from multiple
online sources to create a new result which was not the
original intend of the data.


MASHUPS
create a new one.

•a mashup is an application that combines data from multiple
online sources to create a new result which was not the
original intend of the data.

• data is key!

• tweaking and enriching data is important

• interesting data makes an interesting mashup


MY MUSIC MASHUP.

• http://www.cs.kuleuven.be/~sten/lastonamfm/


COUNTRY & CONTINENT
• why is it useful?

• subgenres
• popularity
• recommendations

• expensive to annotate

• very few existing research

• very hard with signal processing


COUNTRY & CONTINENT
• why is it useful?

• subgenres
• popularity
• recommendations

• expensive to annotate

• very few existing research
!
• very hard with signal processing


IN THE BACKGROUND...
google maps

freebase
last.fm google app
engine
twitter last.fm

last.fm yahoo! pipes last on am/fm

website
dapper youtube


YAHOO! PIPES


LAST.FM


LAST.FM API


FREEBASE

http://www.freebase.com/view/m/01mdm7p

FREEBASE MQL

{
"type" : "/music/album",
"name" : "Synchronicity",
"artist" : "The Police",
"track" : [{
"name":null,
"length":null
}]
}


FREEBASE MQL
{
"type" : "/music/album",
"name" : "Synchronicity",
"artist" : "The Police",
"track" : [
{"name":"Synchronicity II", "length":305.066},
{"name":"Every Breath You Take", "length":254.066},
{"name":"King of Pain", "length":299.066},
{"name":"Wrapped Around Your Finger", "length":313.733},
{"name":"Tea in the Sahara", "length":255.44},
{"name":"Walking in Your Footsteps", "length":216.773},
{"name":"Miss Gradenko", "length":120},
{"name":"Murder by Numbers", "length":276.8},
{"name":"O My God", "length":242.226},
{"name":"Synchronicity I", "length":202.866},
{"name":"Mother", "length":185.64}
]
}


BIOGRAPHIES
• from Last.fm (most of them are
coming from Wikipedia)

• using demonyms.

• “Anders Trentemøller is a
Danish electronic musician.”

• List of demonyms from Wikipedia

http://en.wikipedia.org/wiki/
List_of_adjectival_and_demonymic_forms_of_place_names

computer


The Beatles

computer


The Beatles

Michael Jackson

computer


ABBA
The Beatles

Michael Jackson

computer


ABBA
The Beatles

1

Michael Jackson

computer


ABBA
The Beatles

1

Michael Jackson

2

computer


ABBA
The Beatles

3

1

Michael Jackson

2

computer


RESULTS
• with country we also know continent

• Last.fm and Freebase only contains data for small part
• accuracy:
• Last.fm: 91%
• Freebase: 90%
• Bio: 66%
• Combination: 77%
• more advanced possibilities


THANK YOU!
QUESTIONS?
slides will appear on http://www.slideshare.net/stengovaerts


KU Leuven Music Multimedia Course

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