In this paper, we present an interactive approach for the classification of sound objects in electro-acoustic music. For this purpose, we use relevance feedback combined with active-learning segment selection in an interactive loop. Validation and correction information given by the user is injected in the learning process at each iteration to achieve more accurate classification. Three active learning criteria are compared in the evaluation of a system classifying polyphonic pieces (with a varying degree of polyphony). The results show that the interactive approach achieves satisfying performance in a reasonable number of iterations.

Authors: Gulluni, Sebastien; Essid, Slim; Buisson, Olivier; Richard, Gaël
Affiliations: Institut National de l'Audiovisuel, Bry-sur-Marne Cedex, France; Telecom-Paristech, Paris, France(See document for exact affiliation information.)
AES Conference: 42nd International Conference: Semantic Audio (July 2011)
Paper Number: 6-2
Publication Date: July 22, 2011 Import into BibTeX
Subject: Music Information Retrieval
Permalink: https://www.aes.org/e-lib/browse.cfm?elib=15953

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