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Convention Paper

User Driven, Local Model, Reclassification of Drum Loop Audio Slices

Authors: Lindsay-Smith, Henry; Mcdonald, Skot; Sandler, Mark

AES Convention 130 · Paper 8356 · May 2011

Abstract

We present a method for significantly improving the results of drum loop slice classification. An onset detector is used to slice loops of percussion only audio. Low level features are extracted from the audio slices and the slices are classified into one of seven percussion classes by a previously trained PART decision table. This general classification algorithm shows only an adequate performance. The user is then allowed to correct incorrect classifications. Each corrected classification is combined with a subset of the original classifications and a nearest neighbour algorithm reclassifies the remaining slices according to the corrected local model. The resultant algorithm converges on a 100\% correct solution, with nearly 40% fewer re-classifications than a non-assisted approach.

Details

Published in
AES Convention 130
AES Convention
130
Paper number
8356
Publication date
May 6, 2011
Session subject
Live and Interactive Sound
Affiliation
FXpansion Audio Ltd., London, UK; Queen Mary University of London, London, UK (See document for exact affiliation information.)
Type
Convention Paper