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OFAI-TR-2009-04 ( 2kB PDF file)

A Fast Audio Similarity Retrieval Method for Millions of Music Tracks

Dominik Schnitzer, Arthur Flexer, Gerhard Widmer

We present a filter-and-refine method to speed up acoustic audio similarity queries which use the Kullback-Leibler divergence as similarity measure. The proposed method rescales the divergence and uses a modified FastMap implementation to accelerate nearest-neighbor queries. Overall the method accelerates the search for similar music pieces by a factor of 10 - 30 compared to a linear scan but still offers high recall values (relative to a linear scan) of 95 - 99%. We show how the proposed method can be used to query several million songs for their acoustic neighbors very fast while producing almost the same results that a linear scan over the whole database would return. We present a working prototype implementation which is able to process similarity queries on a 2.5 million songs collection in about half a second on a standard CPU.

Keywords: Music Information Retrieval, Indexing, Audio Similarity

Citation: Schnitzer D., Flexer A., Widmer G.: A Fast Audio Similarity Retrieval Method for Millions of Music Tracks. Technical Report, Österreichisches Forschungsinstitut für Artificial Intelligence, Wien, TR-2009-04, 2009