Automatic reduction of MIDI files preserving relevant musical content

Authors:
Søren Tjagvad Madsen;Rainer Typke;Gerhard Widmer
Affiliations:
Department of Computational Perception, Johannes Kepler University, Linz;Austrian Research Institute for Artificial Intelligence (OFAI), Vienna;Department of Computational Perception, Johannes Kepler University, Linz
Venue:
AMR'08 Proceedings of the 6th international conference on Adaptive Multimedia Retrieval: identifying, Summarizing, and Recommending Image and Music
Year:
2008

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Abstract

Retrieving music from large digital databases is a demanding computational task. The cost of indexing and searching depends on the computational effort of measuring musical similarity, but also heavily on the number and sizes of files in the database. One way to speed up music retrieval is to reduce the search space by removing redundant and uninteresting material in the database. We propose a simple measure of ‘interestingness’ based on music complexity, and present a reduction algorithm for MIDI files based on this measure. It is evaluated by comparing reduction ratios and the correctness of retrieval results for a query by humming task before and after applying the reduction.