Paper: A Comparison Of Alignment Models For Statistical Machine Translation

ACL ID C00-2163
Title A Comparison Of Alignment Models For Statistical Machine Translation
Venue International Conference on Computational Linguistics
Session Main Conference
Year 2000
Authors

In this paper, we t)resent and compare various align- nmnt models for statistical machine translation. We propose to measure tile quality of an aligmnent model using the quality of the Viterbi alignment comt)ared to a manually-produced alignment and de- scribe a refined mmotation scheme to produce suit- able reference alignments. We also con,pare the im- pact of different; alignment models on tile translation quality of a statistical machine translation system.