Paper: Improving Word Alignment using Word Similarity

ACL ID D14-1197
Title Improving Word Alignment using Word Similarity
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2014

We show that semantic relationships can be used to improve word alignment, in ad- dition to the lexical and syntactic features that are typically used. In this paper, we present a method based on a neural net- work to automatically derive word simi- larity from monolingual data. We present an extension to word alignment models that exploits word similarity. Our exper- iments, in both large-scale and resource- limited settings, show improvements in word alignment tasks as well as translation tasks.