A Dimensional Contextual Semantic Model for music description and retrieval
Michele Buccoli, Alessandro Gallo, Massimiliano Zanoni, Augusto Sarti, Stefano Tubaro
Abstract
Several paradigms for high-level music descriptions have been proposed to develop effective system for browsing and retrieving musical content in large repositories. Such paradigms are based on either categorical or dimensional models. The interest in dimensional models has recently grown a great deal, as they define a semantic relation between concepts through graded descriptions. One problem that affects semantic descriptions is the ambiguity that often arises from using the same descriptor in different contexts. In order to overcome this difficulty, it is important to model and address polysemy, which is the property of words to take on different meanings depending on the use-context. In this paper we propose a Dimensional Contextual Semantic Model for defining semantic relations among descriptors in a context-aware fashion. This model is here used for developing a semantic music search engine. In order to evaluate the effectiveness of our model, we compare this engine with two systems that are based on different description models.
BibTeX
@inproceedings{icassp2015_adimensionalcont,
title = {A Dimensional Contextual Semantic Model for music description and retrieval},
author = {Michele Buccoli and Alessandro Gallo and Massimiliano Zanoni and Augusto Sarti and Stefano Tubaro},
booktitle = {ICASSP 2015},
year = {2015}
}