1. A speech recognition system comprising: data storage to store speech training data; and a training engine executed by a processor to: determine consecutive breakout periods in the speech training data, calculate forward and scaled backward probabilities for the breakout periods, determine a convergence time in the training data from some of the scaled backward probabilities, wherein the convergence time is when scaled backward probabilities calculated for some of the breakout periods stop changing, store forward and scaled backward probabilities for the convergence time in the data storage, generate a speech recognition Hidden Markov Model (HMM) from the forward and scaled backward probabilities calculated for the breakout periods, and use the convergence time as an end point for future breakout backward passes conducted for future breakout periods.