Performance of classifiers for Text-independent Speaker Identification With and Without Modelling Through Merging Models
Yussouf Nahayo, Seckin Ari · Sakarya University Journal of Science · 2015
This paper proposes some methods of robust text-independent speaker identification based on Gaussian Mixture Model(GMM). We implemented a combination of GMM model with a set of classifiers such as Support Vector Machine(SVM), K-Nearest Neighbour (K-NN), and Naive Bayes Classifier (NBC). In order to improve the identification rate,we developed a combination of hybrid systems by using validation technique. The experiments were performed on thedialect DR1 of the TIMIT corpus. The results have showed a better performance for the developed technique comparedto the individual techniques.