Integrating Large Context Language Models Into A Real Time Word Recognizer (1996)
| Citations: | 8 - 8 self |
BibTeX
@MISC{Gallwitz96integratinglarge,
author = {F. Gallwitz and E.G. Schukat-Talamazzini and H. Niemann},
title = {Integrating Large Context Language Models Into A Real Time Word Recognizer},
year = {1996}
}
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Abstract
In this paper we present a new recognizer architecture that allows the efficient integration of language models with arbitrary large context information, e.g. polygram models, into the recognition process. Instead of using these models for rescoring the n best word chains generated using bigram information, we extract the best word chain, or optionally the n best word chains, directly from the word lattice using an A* algorithm that incorporates full language model information. For comparison, we developed an improved architecture for fast generation of the n best word chains using bigram information. Experimental results show, that direct incorporation of full language model information increases word accuracy significantly even when compared to rescoring the 1000 best word chains. At the same time, computation time is drastically reduced.
