@inproceedings{,
author={Gosztolya, G{\'a}bor and Kocsor, Andr{\'a}s},
title={Improving the Multi-stack Decoding Algorithm in a Segment-based Speech Recognizer},
abstract={During automatic speech recognition selecting the best hypothesis over a
combinatorially huge hypothesis space is a very hard task, so selecting
fast and efficient heuristics is a reasonable strategy. In this paper a
general purpose heuristic, the multi-stack decoding method, was refined
in several ways. For comparison, these improved methods were tested along
with the well-known Viterbi beam search algorithm on a Hungarian number
recognition task where the aim was to minimize the scanned hypothesis elements
during the search process. The test showed that our method runs 6 times
faster than the basic multi-stack decoding method, and 9 times faster than
the Viterbi beam search method. },
booktitle={Proceedings of 16th Int. Conf. on Industrial and Engineering Applications
of Artificial Intelligence and Expert Systems, IEA/AIE 2003, LNAI vol.
2718},
year={2003},
month={June},
publisher={Springer-Verlag GmbH},
address={Laughborough, UK},
editor={P. W. H. Chung, C. J. Hinde, M. Ali},
pages={744-749}
}