Recently, we proposed an extension to the classical RASTA technique. The new method consists of classical RASTA filtering followed by a phase correction operation. 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. In this paper we introduce an implementation of phase-corrected RASTA suited for real-time processing. In the context of connected digit recognition over the phone using context-independent phone-based models, we show that word error rate for this implementation is more than 20% lower compared to a real-time implementation of the cepstrum mean subtraction channel normalisation method.