Paper: Improving Bitext Word Alignments Via Syntax-Based Reordering Of English

ACL ID P04-3014
Title Improving Bitext Word Alignments Via Syntax-Based Reordering Of English
Venue Annual Meeting of the Association of Computational Linguistics
Session System Demonstration
Year 2004
Authors

We present an improved method for automated word alignment of parallel texts which takes advantage of knowledge of syntactic divergences, while avoid- ing the need for syntactic analysis of the less re- source rich language, and retaining the robustness of syntactically agnostic approaches such as the IBM word alignment models. We achieve this by using simple, easily-elicited knowledge to produce syntax- based heuristics which transform the target lan- guage (e.g. English) into a form more closely resem- bling the source language, and then by using stan- dard alignment methods to align the transformed bitext. We present experimental results under vari- able resource conditions. The method improves word alignment performance for language pairs such as English-Korean and English-Hindi, which...