Algorithms for an optimal A search and linearizing the search in the stack decoder

Authors:
Douglas B. Paul
Affiliations:
-
Venue:
HLT '90 Proceedings of the workshop on Speech and Natural Language
Year:
1990

Citing 3
Cited 2

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Abstract

The stack decoder is an attractive algorithm for controlling the acoustic and language model matching in a continuous speech recognizer. It implements a best-first tree search of the language to find the best match to both the language model and the observed speech. This paper describes a method for performing the optimal A search which guarantees to find the most likely path (recognized sentence) while extending the minimum number of stack entries. A tree search, however, is exponential in the number of words. A second algorithm is presented which linearizes the search at the cost of approximating some of the path likelihoods.