MiniVectors: an Improved GMM-SVM Approach for Speaker Verification

The accuracy levels achieved by state-of-the-art Speaker Verification systems are high enough for the technology to be used in real-life applications. Unfortunately, the transfer from the lab to the field is not as straight-forward as could be: the best performing systems can be computationally expensive to run and need large speaker model footprints. In this paper, we compare two speaker verification algorithms (GMM-SVM Supervectors and Kharroubi’s GMM-SVM vectors) and propose an improvement of Kharroubi’s system that: (a) achieves up to 17% relative performance improvement when compared to the Supervectors algorithm; (b) is 24% faster in run time and (c) makes use of speaker models that are 94% smaller than those needed by the Supervectors algorithm.