In today's world, there are more and more risks of fraud such as spoofing. It is necessary to fight against these risks and to restore trust between the client and the company providing the services. With the advent of artificial intelligence, it is now possible to reduce these types of risks through new authentication methods, such as speaker recognition using machine learning (ML) like neural network techniques. This Recommendation addresses telebiometric authentication using speaker recognition technologies. It introduces first a speaker recognition system and provides functional requirements for each subsystem of the speaker recognition system. Then different models for implementing telebiometric speaker authentication are described, including the case of integrating with voice assistant devices, e.g., smart speaker. This Recommendation identifies threats and vulnerabilities at each step of the telebiometric speaker authentication, including speech presentation, feature extraction, comparison and decision-making. It also provides countermeasures for the identified threats at each step of the telebiometric authentication.