Voice-Based Multi-Factor Authentication Security System

Abstract

Voice biometrics use the unique vocal attributes of a user to secure physical, virtual, and online assets. Current voice biometric systems use cloud data centers to pro cess voice samples received from computers or mobile devices[1]. However, in the near future, it will be possible to use programmable voice biometric chips that can leverage pre-trained machine learning models to operate autonomously. Such chips would make it possible to deploy voice biometric systems more widely to secure physical assets without the need for internet connections[2]. This project introduces a voice biometric system tailored for home or office security applications. The system’s core functionality involves detecting and verifying user voices by processing multiple instances of wake-up words presented as 4-digit pass codes. Designed to authenticate various users, the project progressed through stages that encompassed researching and evaluating diverse voice extraction methods. The optimal method was selected for the system. Subsequently, speaker recognition and spoken digit classification models were implemented and assessed. The study achieved significant milestones by rigorously testing, simulating, accelerating, and deploying the models onto hardware, yielding promising results and advancements.