Methods and systems for training a machine learning model and authenticating a user with the model

Abstract

A method of training a machine learning model to conduct authentication transactions is provided that includes the steps of obtaining, by an electronic device, a training dataset of audio signals. Each audio signal includes voice biometric data of a user and information for a passphrase spoken by the respective user and belongs to a same or different data class. Each data class includes a user identity and a passphrase identifier. Moreover, the method includes the steps of creating, using a machine learning model being trained, at least one embedding for each audio signal. The machine learning model includes parameters. Furthermore, the method includes calculating, by a machine learning algorithm using the embeddings, a loss, and updating parameters of the machine learning model based on the calculated loss. In response to determining criteria defining an end of training have been satisfied, deeming the machine learning model to be operable for use in simultaneously successfully verifying the identity of a user based on voice biometric data and verifying a passphrase spoken by the user matches a secret passphrase during authentication transactions.