An Improved Pruning Method Based on the Number of States Possessed by Hypotheses

This paper presents an improved pruning method taking into account of the number of states possessed by hypotheses in some certain frames. With conventional pruning strategy, the hypotheses with a low score or a bad ranking will be discarded. However, it neglects a fact that the hypotheses several states ahead of or behind the right hypothesis in the prefix tree, which should be discarded, have similar scores and rankings with the right hypothesis. If a state is part of a partial path hypothesis, we say it is possessed by the hypothesis. So in a speech frame, we can deduce that the hypotheses which possess the most states and the hypotheses which possess the least states have little chance to be the right hypothesis. The proposed method analysis the range of the number of the states possessed by the hypotheses, and discards the hypotheses that possess too many or too few states. According to the experiments, This method could effectively improve the performance of the ASR.