A novel approach of speaker authentication by fusion of speech and image features using Artificial Neural Networks

Abstract

This paper presents a decision fusion technique for a bimodal biometric verification system that makes use of facial and speech biometrics. This report considers multimodal biometric systems and their applicability to access control, authentication and security applications. We have simulated three Artificial Neural Network (ANN) models: firstly, speaker identification by speech parameters, secondly person identification by image parameters and finally the person authentication by fusion of speech and image feature. All the three ANN models are trained by Back-propagation algorithm.