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A comparison of alignment models for statistical machine translation

Published 1 January 2000Open access
Franz Josef Och, Hermann Ney
Citations214
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TL;DR

The quality of an alignment model is proposed to be measured using the quality of the Viterbi alignment compared to a manually-produced alignment and a refined annotation scheme to produce suitable reference alignments is described.

Abstract

In this paper, we present and compare various alignment models for statistical machine translation. We propose to measure the quality of an alignment model using the quality of the Viterbi alignment compared to a manually-produced alignment and describe a refined annotation scheme to produce suitable reference alignments. We also compare the impact of different alignment models on the translation quality of a statistical machine translation system.

Keywords

Computer Science