Using vector quantization in Automatic Speaker Verification

Abstract

This article investigates several technique based on vector quantization (VQ) and maximum a posteriori adaptation (MAP) in Automatic Speaker Verification ASV. We propose to create multiple codebooks of Universal Background Model UBM by Vector Quantization and compare them with traditional approach in VQ, MAP adaptation and Gaussian Mixture Models.