Speaker Recognition Techniques: A Review
Satyam P. Todkar, Snehal S. Babar, Rudrendra U. Ambike, Prasad B. Suryakar, Jayashree Rajesh Prasad · 2018
Speaker Recognition is the process of recognizing the speaker from the individual's speech biometrics. The voice characteristics of every speaker are different and thus can be used to construct a model. This model is later used to recognize an enrolled speaker from the list of available speakers. The paper makes an effort to discuss different speaker modeling techniques like Vector Quantization (VQ), Gaussian Mixture Model (GMM)., Neural Networks (NN)., etc. Also., different techniques for extraction of voice characteristics like Mel Frequency Cepstral Coefficients (MFCC), Linear Predictive Coding (LPC) are discussed. Further, an in-depth analysis of these surveyed techniques is made to identify their advantages and limitations. The work in the field of Speaker Recognition Systems began in the 1950's and is evolving since then, it has wide applications in the fields of security, forensics., authentication etc.