This publication addresses the identification of drum patterns and the classification of their musical genres. Drum patterns are estimated from audio data automatically. This process involves the transcription of percussive un-pitched instruments with a method based on Independent Subspace Analysis and a robust estimation of tatum grid and musical meter. Subsequently, patterns are identified from histograms, describing the frequency of occurrence of the percussive events on distinct metric positions. Various high-level features are derived from the drum patterns by identifying typical playing styles. The classification procedure evaluates these features in combination with information on musical meter and occurring instruments.

Author: Dittmar, Christian
Affiliation: Fraunhofer Institute for Digital Media Technology IDMT, Ilmenau, Germany
AES Conference: 25th International Conference: Metadata for Audio (June 2004)
Paper Number: 6-1
Publication Date: June 1, 2004 Import into BibTeX
Subject: Metadata for Audio
Permalink: https://www.aes.org/e-lib/browse.cfm?elib=12818

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