Discriminitive Multi-Resolution Sub-Band and Segmental Phonetic Model Combination

Abstract

A joint discriminative framework for multi-resolution sub-band HMMs and a hybrid segmental phonetic model is presented which combines independent likelihood scores using class dependent weightings trained to a minimum classification error criteria. This successfully extends the performance on a phonetic classification task to 76.3% compared to a full-band HMM score of 69.2%