In this paper we introduce a well-motivated abstract pruning criterion for LVCSR decoders based on the anticipated recombination of HMM state alignment paths. We show that several heuristical pruning methods common in dynamic network decoders are approximations of this pruning criterion. The abstract criterion is too complex to be applied directly in an efficient manner, so we derive approximations which can be applied efficiently. Our new pruning methods allow much more exhaustive pruning of the search space than previous methods. We show that the size of the search space can be reduced by up to 50% at equal precision over the previous state of the art, and the RTF by 20%. The abstract pruning criterion can be considered a guide to derive effective pruning methods for any kind of time synchronous decoder.

Index Terms: speech recognition, search, pruning