Adaptive Multi-Modal Person Verification System
Conrad Sanderson, Kuldip K. Paliwal · 2000
This paper describes an adaptive multi-modal person verification system based on speech and face images. The system adapts to noise present in the speech signal by modifying the parameters of the fusion module. Linear and Support Vector Machine (SVM) based techniques of fusing the similarity measures from speech and face modes are investigated. Experimental results obtained on the Digit Database show that the adaptive system significantly outperforms its non-adaptive counterpart. 1. INTRODUCTION A person verification system attempts to verify the claimed identity of an individual. This can be useful in situations where security considerations preclude obtaining access by simpler means such as a key. Recently, multi-modal person verification systems have become popular [1], where similarity measures from different modality experts are fused before the final decision to accept or reject a claimant is made. The attraction of multi-modal systems stems from their ability to have better pe...