Hybrid AI-based Voice Authentication

Abstract

Biometric authentication systems reveal individuals' physical or behavioral uniqueness and identify them by comparing them with existing records. Today, many biometric recognition systems, such as fingerprint reading, palm reading, and face reading, are being studied and used. The human voice is also among the techniques used for this purpose. Due to this feature, the human voice performs secure transactions and authentication in various fields. Based on these voice features, we used a dataset of 66,569 voice recordings. The voice recordings were revised to include six sentences of at least six words each from 24 different people to get the maximum benefit from the dataset. The voices in the reduced dataset were labeled as sentences belonging to the same person and sentences belonging to different people and converted into matrix form. A biometric recognition study resulted in a correlation score of 0.88. As a result of these processes, the feasibility of a voice biometric recognition system with artificial intelligence has been demonstrated.