Mandarin-Sichuan dialect bilingual text-independent speaker verification using GMM

Abstract

Due to the mismatch between mandarin and Sichuan dialect in training and test stages,the performance of speaker verification system degrades dramatically.To solve this problem,a combined Gaussian Mixture Model(GMM),which is trained by proportional pooling mandarin and Sichuan dialect,was presented in this paper.Compared with the Gaussian mixture model trained solely using mandarin/Sichuan dialect,the combined Gaussian mixture model described the characteristic of speaker from both mandarin and Sichuan dialect.Experiments on a self-built mandarin-Sichuan dialect speech database demonstrate that the introduced combined Gaussian mixture model is more robust for speech mismatching between mandarin and Sichuan dialect.A proper proportion between pooling mandarin and Sichuan dialect speech was also provided.