Improving fast-align by reordering

Abstract

Fast-align is a simple, fast, and efficient approach for word alignment based on the IBM model 2. fast.align performs well for language pairs with relatively similar word orders; however, it does not perform well for language pairs with drastically different word orders. We propose a segmenting-reversing reordering process to solve this problem by alternately applying fast-align and reordering source sentences during training. Experimental results with Japanese-English translation demonstrate that the proposed approach improves the performance of fast-align significantly without the loss of efficiency. Experiments using other languages are also reported.