Audio Features Affected by Music Expressiveness
May 17, 2016 Β· Declared Dead Β· π Annual International ACM SIGIR Conference on Research and Development in Information Retrieval
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Authors
Alberto Introini, Giorgio Presti, Giuseppe Boccignone
arXiv ID
1605.05369
Category
cs.IR: Information Retrieval
Cross-listed
cs.SD
Citations
0
Venue
Annual International ACM SIGIR Conference on Research and Development in Information Retrieval
Last Checked
4 months ago
Abstract
Within a Music Information Retrieval perspective, the goal of the study presented here is to investigate the impact on sound features of the musician's affective intention, namely when trying to intentionally convey emotional contents via expressiveness. A preliminary experiment has been performed involving $10$ tuba players. The recordings have been analysed by extracting a variety of features, which have been subsequently evaluated by combining both classic and machine learning statistical techniques. Results are reported and discussed.
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