Phase-corrected RASTA for automatic speech recognition over the phone
Johan de Veth, Lou Boves · 2002
In this paper we propose an extension to the classical RASTA technique. The new method consists of classical RASTA filtering followed by an all-pass phase correction filter. In this manner, the influence of the communication channel is as effectively removed as with classical RASTA. However, our proposal does not introduce a left-context dependency like classical RASTA. Therefore the new method is better suited for automatic speech recognition based on context-independent modeling with Gaussian mixture hidden Markov models. We tested this in the context of connected digit recognition over the phone. In case we used context-dependent hidden Markov models (i.e., word models), we found that classical RASTA and phase-corrected RASTA performed equally well. For context-independent phone-based models, we found that phase-corrected RASTA can outperform classical RASTA depending on the acoustic resolution of the models.