A Finite-State Approach to Machine Translation

@inproceedings{Bangalore2001AFA,
  title={A Finite-State Approach to Machine Translation},
  author={Srinivas Bangalore and Giuseppe Riccardi},
  booktitle={NAACL},
  year={2001}
}
The problem of machine translation can be viewed as consisting of two subproblems (a) Lexical Selection and (b) Lexical Reordering. We propose stochas-tic nite-state models for these two subproblems in this paper. Stochastic nite-state models are ee-ciently learnable from data, eeective for decoding and are associated with a calculus for composing models which allows for tight integration of constraints from various levels of language processing. We present a method for learning stochastic nite… CONTINUE READING
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