Metadata for Audio 25th International AES Conference 17th to 19th June 2004 London UK
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Metadata for Audio

Poster CD5-3

Automatic Optimization of a Musical Similarity Metric Using Similarity Pairs

Thorsten Kastner, Eric Allamanche, Oliver Hellmuth, Christian Ertel, Marion Schalek, Jürgen Herre
Fraunhofer IIS, Ilmenau, Germany

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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