Biometric verification based on voice data

The verification of call center customers based on voice data as a part of multi-factor authentication for security improvement.

We used deep neural architecture for comparing voice prints from a database, with high verification accuracy.

We built and trained an efficient ML model using a deep neural architecture to compare incoming voice data with voice samples from the previously formed database.
The security of the authentication system has been enhanced; the time for processing and comparing voice samples has been reduced; and the estimated accuracy of verification has been improved.
Low EER (Exact Error Rate) was achieved.