Applying Statistical English Language Modeling to Symbolic Machine Translation
نویسندگان
چکیده
The PANGLOSS Mark III system [Frederking et al. 94] was from the outset designed to be a symbolic, human-aided machine translation (MT) system. The need arose to rapidly adapt it for use as a fully-automated MT system. Our solution to this problem was to add a statistical English language model (ELM) to replace the most significant user activity, selecting between alternate translations produced by the system. The language model used is a trigram model with backoff to bigram and unigram probabilities. The language modeling and search procedure are described in detail, and comparison is made to other trigram-based statistical MT work.
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