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Convention Paper

Application of Fisher Linear Discriminant Analysis to Speech/Music Classification

Authors: Alexandre, Enrique; Cuadra-Rodríguez, Lucas; Gil-Pita, Roberto; Rosa-Zurera, Manuel

AES Convention 120 · Paper 6678 · May 2006

Abstract

This paper proposes the application of Fisher linear discriminants to the problem of speech/music classification. Fisher linear discriminants can classify between two different classes, and are based on the calculation of some kind of centroid for the training data corresponding with each one of these classes. Based on that information a linear boundary is established, which will be used for the classification process. Some results will be given demonstrating the superior behavior of this classification algorithm compared with the well-known K-nearest neighbor algorithm. It will also be demonstrated that it is possible to obtain very good results in terms of probability of error using only one feature extracted from the audio signal, being thus possible to reduce the complexity of this kind of systems in order to implement them in real-time.

Details

Published in
AES Convention 120
AES Convention
120
Paper number
6678
Publication date
May 6, 2006
Session subject
Analysis and Synthesis of Sound; Mobile Phone Audio; Automobile Audio
Affiliation
Universidad de Alcalá (See document for exact affiliation information.)
Type
Convention Paper