Data duration and model size dependency of GMM- and SVM-based speaker verification performance

This study aims to present two methods for speaker verification problem using Gaussian mixture models and support vector machines over the CSLU speaker recognition database. The performance of these two classifiers for various training and test data durations and model sizes are compared. The effect of score fusion on verification error rates is investigated.