Context-Dependent MLPs

Chapters 7 and 8 have shown the ability of Multilayer Perceptrons (MLPs) to estimate emission probabilities for Hidden Markov Models (HMM). In these chapters, we have shown that these estimates led to improved performance over standard estimation techniques when a fairly simple HMM was used. However, current state-of-the-art continuous speech recognizers require HMMs with greater complexity, e.g., multiple densities per phone and/or context-dependent phone models. Will the consistent improvement we have seen in these tests be washed out in systems with more detailed models?