Comparative Analysis of Music Recordings from Western and Non-Western traditions by Automatic Tonal Feature Extraction
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Date
2008-07
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
Empirical Musicology Review
Abstract
The automatic analysis of large musical corpora by means of
computational models overcomes some limitations of manual analysis, and the
unavailability of scores for most existing music makes necessary to work with audio
recordings. Until now, research on this area has focused on music from the Western
tradition. Nevertheless, we might ask if the available methods are suitable when
analyzing music from other cultures. We present an empirical approach to the
comparative analysis of audio recordings, focusing on tonal features and data mining
techniques. Tonal features are related to the pitch class distribution, pitch range and
employed scale, gamut and tuning system. We provide our initial but promising results
obtained when trying to automatically distinguish music from Western and non-
Western traditions; we analyze which descriptors are most relevant and study their
distribution over 1500 pieces from different traditions and styles. As a result, some
feature distributions differ for Western and non-Western music, and the obtained
classification accuracy is higher than 80% for different classification algorithms and an
independent test set. These results show that automatic description of audio signals
together with data mining techniques provide means to characterize huge music
collections from different traditions and complement musicological manual analyses.
Description
Keywords
audio description, tonality, machine learning, comparative analysis
Citation
Empirical Musicology Review, v3 n3 (July 2008), 140-156