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Convention Paper

Training-Based Semantic Descriptors Modeling for Violin Quality Sound Characterization

Authors: Zanoni, Massimiliano; Setragno, Francesco; Antonacci, Fabio; Sarti, Augusto; Fazekas, György; Sandler, Mark B.

AES Convention 138 · Paper 9353 · May 2015

Abstract

Violin makers and musicians describe the timbral qualities of violins using semantic terms coming from natural language. In this study we use regression techniques of machine intelligence and audio features to model in a training-based fashion a set of high-level (semantic) descriptors for the automatic annotation of musical instruments. The most relevant semantic descriptors are collected through interviews to violin makers. These descriptors are then correlated with objective features extracted from a set of violins from the historical and contemporary collections of the Museo del Violino and of the International School of Luthiery both in Cremona. As sound description can vary throughout a performance, our approach also enables the modeling of time-varying (evolutive) semantic annotations.

Details

Published in
AES Convention 138
AES Convention
138
Paper number
9353
Publication date
May 6, 2015
Session subject
Semantic Audio
Affiliation
Politecnico di Milano, Milan, Italy; Queen Mary University of London, London, UK (See document for exact affiliation information.)
Type
Convention Paper