DocumentCode :
3433684
Title :
Application of combining classifiers for text-independent speaker identification
Author :
Boujelbene, S. Zribi ; Ben Ayed Mezghani, D. ; Ellouze, N.
Author_Institution :
Dept. Comput. Sci., Fac. of Humanities & Social Sci. of Tunis, Tunis, Tunisia
fYear :
2009
fDate :
13-16 Dec. 2009
Firstpage :
723
Lastpage :
726
Abstract :
Speaker recognition systems usually need a feature extraction stage witch aims at obtaining the best signal representation. States of the art, speaker identification systems are based on a cepstral feature extraction follow by an individual classifier or a hybrid classifier. Nowadays, an alternative approach consists in fusing different features or different classifiers are increasingly used. In this paper, different features are defined. Each feature is modeled using the Gaussian mixture model and construct a speakers´ models dictionary. These dictionaries are used by the multilayer perceptron (MLP) classifier, the support vector machines (SVM) classifier and the decision trees (DT) classifier for matching and the scores (outputs) of all classifiers are then considered for combination. Results indicate that the use of combining classifiers with different features is an effective way to attack the problem of text-independent speaker identification.
Keywords :
Gaussian processes; multilayer perceptrons; speaker recognition; support vector machines; Gaussian mixture model; cepstral feature extraction; decision trees classifier; hybrid classifier; multilayer perceptron classifier; signal representation; speaker models dictionary; speaker recognition systems; support vector machines classifier; text-independent speaker identification; Cepstral analysis; Classification tree analysis; Decision trees; Dictionaries; Feature extraction; Multilayer perceptrons; Signal representations; Speaker recognition; Support vector machine classification; Support vector machines;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electronics, Circuits, and Systems, 2009. ICECS 2009. 16th IEEE International Conference on
Conference_Location :
Yasmine Hammamet
Print_ISBN :
978-1-4244-5090-9
Electronic_ISBN :
978-1-4244-5091-6
Type :
conf
DOI :
10.1109/ICECS.2009.5410793
Filename :
5410793
Link To Document :
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