  This paper presented our work on applying Recurrent Deep Stacking Networks
(RDSNs) to Robust Automatic Speech Recognition (ASR) tasks. In the paper, we
also proposed a more efficient yet comparable substitute to RDSN, Bi- Pass
Stacking Network (BPSN). The main idea of these two models is to add
phoneme-level information into acoustic models, transforming an acoustic model
to the combination of an acoustic model and a phoneme-level N-gram model.
Experiments showed that RDSN and BPsn can substantially improve the
performances over conventional DNNs.
