Improving the multi-stack decoding algorithm in a segment-based speech recognizer

Authors:
Gábor Gosztolya;András Kocsor
Affiliations:
Research Group on Artificial Intelligence of the Hungarian Academy of Sciences and University of Szeged, Szeged, Hungary;Research Group on Artificial Intelligence of the Hungarian Academy of Sciences and University of Szeged, Szeged, Hungary
Venue:
IEA/AIE'2003 Proceedings of the 16th international conference on Developments in applied artificial intelligence
Year:
2003

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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 multistack decoding method, and 9 times faster than the Viterbi beam search method.