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
Subject: Music Information Retrieval

Click to purchase paper as a non-member or you can login as an AES member to see more options.

No AES members have commented on this paper yet.

Subscribe to this discussion

To be notified of new comments on this paper you can subscribe to this RSS feed. Forum users should login to see additional options.

Start a discussion!

If you would like to start a discussion about this paper and are an AES member then you can login here:
Username:
Password:

If you are not yet an AES member and have something important to say about this paper then we urge you to join the AES today and make your voice heard. You can join online today by clicking here.