Combination of Rule-Based and Data-Driven Fusion Methodologies for Different Speaker Verification Modes of Operation
Saeid Safavi, Iosif Mporas · 2017
In this paper we present three methodologies for the fusion of different speaker verification modes of operation. Specifically, we investigate a knowledge-based (rule-based) method, based on biometrics and security knowledge, a data-driven method, based on machine learning fusion models and a combination of them. The experimental results indicate that the hybrid fusion architecture, which is the combination of knowledge-based and data-driven based fusion, offers both robustness against spoofing and improvement in speaker verification performance.