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Content-Based Music Retrieval and Visualization System for Ethnomusicological Music Archives

  • Michael BlaßEmail author
  • Rolf Bader
Chapter
Part of the Current Research in Systematic Musicology book series (CRSM, volume 5)

Abstract

In this chapter we propose a content-based exploration and visualization system for ethnomusicological archives that allows for data access by rhythm similarity. The system extracts an onsets-synchronous timbre feature of each audio file of a given collection. From the resulting time series, Hidden Markov Model are trained. The transition probability matrices of the models are considered a rhythm fingerprint that represents the musics rhythmic structure in terms of timbre. The self-organizing map algorithm is utilized to project the high-dimensional fingerprints onto a two-dimensional map. This technique preserves the topology of the high-dimensional feature space, which results in similar map positions for similar rhythms. A clustering by rhythm similarity is thus achieved. The system, therefore, supports musicologist studies in several ways: the rhythm fingerprinting does neither imply a certain theory of music nor introduce cultural bias. Hence, different musics can be compared meaningfully regardless of their origin. Retrieval by similarity allows for an explorative approach to the music collections, which can support researchers in finding new hypothesis and utilizing music archives with few or without meta data. The system is currently prototyped in the Ethnographic Sound Recordings Archive of the University of Hamburg as a part of the COMSAR project.

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.HamburgGermany

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