In large vocabulary continuous speech recognizers the search space needs to be constrained efficiently to make the recognition task feasible. Beam pruning and restricting the number of active paths are the most widely applied techniques for this. In this paper, we present three additional pruning criteria, which can be used to further limit the search space. These new criteria take into account the state of the search space, which enables tighter pruning. In the speech recognition experiments, the new pruning criteria were shown to reduce the search space up to 50% without affecting the search accuracy. We also present a method for optimizing the threshold parameters of the pruning criteria for the selected level of recognition accuracy. With this method even a large number of different pruning thresholds can be determined with little effort.
Cite as: Pylkkönen, J. (2005) New pruning criteria for efficient decoding. Proc. Interspeech 2005, 581-584, doi: 10.21437/Interspeech.2005-346
@inproceedings{pylkkonen05_interspeech,
author={Janne Pylkkönen},
title={{New pruning criteria for efficient decoding}},
year=2005,
booktitle={Proc. Interspeech 2005},
pages={581--584},
doi={10.21437/Interspeech.2005-346}
}