An overview of speaker recognition

Abstract

Speaker recognition has been studied for many years and has been a hot topic. This paper presents an overview of speaker recognition methods, which include the classical and the state-of-art methods. According to the modular components of speaker recognition system, we firstly introduced the fundamentals of speaker recognition, which are mainly divided into two parts: feature extraction and speaker modeling. The most commonly speech features used in speaker recognition were elaborated firstly. In particular, the recent progress of deep neural network proposes a new approach of feature extraction and has become the technology trend. Secondly, the classical approaches of speaker recognition model were introduced, and elaborated the recent progress of deep learning speaker recognition. This paper especially provides an in-depth analysis on end-to-end model which consists of a training component to extract features, an enrollment component to training the speaker model, and an evaluation component with appropriate loss function for optimization. The final part concludes the paper with discussion on future trends.