Sampling and optimization in phrase-based machine translation using an enriched language model representation

摘要

Rejection sampling is performed to acquire at least one target language translation for a source language string s in accordance with a phrase-based statistical translation model p(x) = p(t, a | s ) where t is a candidate translation, a is a candidate alignment comprising a biphrase sequence generating the candidate translation t, and x is a sequence representing the candidate alignment a. The rejection sampling uses a proposal distribution comprising a weighted finite state automaton (WFSA) q ( n ) that is refined responsive to rejection of a sample x * obtained in a current iteration of the rejection sampling to generate a refined WFSA q (n+1) for use in a next iteration of the rejection sampling. The refined WFSA q (n+1) is selected to satisfy the criteria p(x) ‰¤ q ( n +1) (x) ‰¤ q ( n ) (x) for all x ˆˆ X and q ( n +1) ( x *) < q ( n ) ( x *) where the space X is the set of sequences x corresponding to candidate alignments a that generate candidate translations t for the source language string s.