The truncation error for a two-pass decoder is analyzed in a problem of phonetic speech recognition for very demanding latency constraints (look-ahead length < 100ms) and for applications where successive refinements of the hypotheses are not allowed. This is done empirically in the framework of hybrid MLP/HMM models. The ability of recurrent MLPs, as a posteriori probability estimators, to model time variations is also considered, and its interaction with the dynamic modeling in the decoding phase is shown in the simulations.