Linear trajectory models incorporating preprocessing parameters for speech recognition

摘要

The proposed model aims at finding an optimal linear transformation on the Mel-warped DFT features according to the minimum classification error (MCE) criterion. This linear transformation, along with the (NSHMM) parameters, are automatically trained using the gradient descent method. An advantageous error rate reduction can be realized on a standard 39- class TIMIT phone classification task in comparison with the MCE-trained NSHMM using conventional preprocessing techniques.