Benefit of Maximum Likelihood Linear Transform (MLLT) used at different levels of covariance matrices clustering in ASR systems

Abstract

The paper discusses the benefit of a Maximum Likelihood Linear Transform (MLLT) applied on selected groups of covariance matrices. The matrices were chosen and clustered using phonetic knowledge. Results of experiments are compared with outcomes obtained for diagonal and full covariance matrices of a baseline system and also for widely used transforms based on Linear Discriminant Analysis (LDA), Heteroscedastic LDA (HLDA) and Smoothed HLDA (SHLDA). © Springer-Verlag Berlin Heidelberg 2007.