Word Alignment by Thresholded Two-Dimensional Normalization.
Hamidreza Kobdani, Alexander Fraser, Hinrich Schütze · 2009
In this paper, we present 2D-Linking, a new unsupervised method for word alignment that is based on association scores between words in a bitext. 2D-Linking can align m-to-n units. It is very efficient because it requires only two passes over the data and less memory than other methods. We show that 2D-Linking is superior to competitive linking and as good as or better than symmetrized IBM Model 1 in terms of alignment quality and that it supports trading off precision against recall. 1