Abstract
This thesis is on the subject of content based music playlist generation systems.
The primary aim is to develop algorithms for content based music playlist
generation that are faster than the current state of technology while keeping
the quality of the playlists at a level that is at least comparable with that of the
current state of technology. Not only need the algorithms be fast, they shall
also allow flexibility for the end user to be able to tune the algorithms to match
his personal requirements. For evaluation of the algorithms, a framework for
automatic content based music playlist generation is developed and presented.
In order to be able to evaluate the quality of music playlist generation
systems, criteria for quality judgment of playlists have to be known. To gain
insight in these quality criteria, a questionnaire is developed. The responses on
this questionnaire are analysed. It shows that the number of parameters that
influence the perceived quality of a personal playlist is huge, and the individual
variation of desired values is large. Because of the large variance in preferred
values, it is impossible to find one single set of parameters that suits for all
people. Using the results of the questionnaire, it is argued that playlist genre
consistency is a suitable criterion for assessing playlist quality. Songs within
a playlist should have approximately the same genre. The key to good music
playlist generation systems therefore is a good music similarity measure, that
allows finding ‘similar’ music. To speed up music playlist generation systems,
the music similarity measures used by these systems should be fast. This thesis
presents two steps towards faster music similarity measures.
Original language | English |
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Qualification | Doctor of Philosophy |
Awarding Institution |
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Supervisors/Advisors |
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Thesis sponsors | |
Award date | 27 Aug 2009 |
Place of Publication | Enschede |
Publisher | |
Print ISBNs | 978-90-365-2886-3 |
DOIs | |
Publication status | Published - 27 Aug 2009 |
Keywords
- IR-67365
- METIS-266939
- EWI-19802
- content based music playlist