This paper discusses a transition from the traditional methods to novel deep learning architectures for speaker recognition. The article aims to compare the traditional statistical methods and new approaches using deep learning models. To articulate the difference in the discussed approaches it furthermore describes several recent methods of optimization and evaluation techniques. The review covers datasets used, results, contributions made toward speaker recognition, and limitations related to it.