Automatische Erkennung von Cover-Versionen und Plagiaten in ...

Abstract
This thesis is dedicated to the automatic detection of different versions of one piece of
music. In order to carry out such classification tasks it is necessary to extract meaningful
characteristic from given data. Besides two known approaches that refer to the whole
piece, two new ones are introduced. Those features are based on the idea that a song
is represented by its chorus only. This thesis describes all the necessary steps as well as
relevant basics in order to extract those four features from arbitrary audio signals.
Based upon the computed features the actual classification task can be performed. It
is to decide whether two compared pieces of music are independent from each other
or not. As well as the Dynamic Time Warp algorithm, which is know from the field
of speech processing, another approach is introduced. It is based upon the assumption
that the variation in tempo is constant between two versions of on piece of music.
All possible combinations of features and classification methods are evaluated and dis-
cussed using an experimental prototype. This thesis is completed by a brief recapitula-
tion and some prospects for future work.
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