Metadata for Audio
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Poster CD5-3
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Automatic Optimization of a Musical Similarity
Metric Using Similarity Pairs
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Thorsten Kastner,
Eric Allamanche, Oliver Hellmuth, Christian Ertel,
Marion Schalek, J�rgen Herre
Fraunhofer IIS,
Ilmenau, Germany
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| With the growing amount of multimedia data available
everywhere and the necessity to provide efficient
methods for browsing and indexing this plethora of audio
content, automated musical similarity search and
retrieval has gained considerable attention in recent
years. This paper presents a system which combines a
set of perceptual low-level features with appropriate
classification schemes for the task of retrieving similar
sounding songs in a database. A methodology for analyzing
the classification results to avoid time consuming
subjective listening tests for an optimum feature selection
and combination is presented. It is based on a
calculated "similarity index" that reflects the similarity
between specifically embedded similarity pairs. The
system�s performance as well as the usefulness of the
analyzing methodology is evaluated through a subjective
listening test. |
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