Deepfake detection

A computer-implemented method for authenticating users based on speech of audio signals, comprising:

• receiving, by a computer via a first communication channel for a resource, a user authentication request for accessing the resource including authentication credentials for a first authentication;
• obtaining, by the computer via a second communication channel, responsive to successfully authenticating a user according to the first authentication using the authentication credentials, an audio speech signal of the user for a second authentication;
• extracting, by the computer, a plurality of features from the audio speech signal, including one or more audio background features;
• generating, by the computer, a plurality of initial liveness scores using the plurality of features by applying a plurality of machine-learning models of a machine-learning architecture to the plurality of features extracted from the audio speech signal, wherein each machine-learning model of the machine-learning architecture is trained to generate a corresponding initial liveness score of the plurality of initial liveness scores using a corresponding subset of features of the plurality of features extracted from the audio speech signal, the initial liveness scores including a first initial liveness score indicating an audio background change generated using at least one subset of features having the one or more audio background features from the plurality of features;
• generating, by the computer, based upon the plurality of initial liveness scores generated using the plurality of features extracted from the audio speech signal via the second communication channel, a liveness score indicating a likelihood that the user is a human speaker;
• and
• executing, by the computer, the second authentication to determine whether to permit the user access to the resource of the first communication channel based upon comparing the liveness score against a threshold.