Effectiveness of phase-corrected rasta for continuous speech recognition
Johan de Veth, Louis Boves · 1998
Phase-corrected RASTA is a new technique for channel normalization that consists of classical RASTA filtering followed by a phase correction operation. In this manner, the channel bias is as effectively removed as with classical RASTA, without introducing a left context dependency. The performance of the phase-corrected RASTA channel normalization technique was evaluated for a continuous speech recognition task. Using context-independent hidden Markov models we found that phase-corrected RASTA reduces the best-sentence word error rate (WER) by 23% compared to classical RASTA. For contextdependent models phase-corrected RASTA reduces WER by 15% compared to classical RASTA. 1. INTRODUCTION In order to reduce the linear filtering effect of communication channels, different channel normalization (CN) techniques have been proposed (e.g. [1, 2, 3]). Recently, a new, extended version of the classical RASTA filtering technique was proposed and tested in the context of connected digit recogn...