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This paper reviews a line of research carried out over the last decade in speech recognition assisted by discriminatively trained, feedforward networks. The particular focus is on the use of multiple layers of processing preceding the hidden Markov model based decoding of word sequences. Emphasis is placed on the use of multiple streams of highly dimensioned layers, which have proven useful for this purpose. This paper ultimately concludes that while the deep processing structures can provide improvements for this genre, choice of features and the structure with which they are incorporated, including layer width, can also be significant factors.