Transferring Syntactic Relations from English to Hindi Using Alignments on Local Word Groups.

Various works have used word alignments in parallel corpora to transfer information like POS tags, syntactic trees and word senses from source to target sentences. In this paper, we work on the problem of projecting syntactic relations from English to morphologically rich Hindi parallel text. We show the effectiveness of Local Word Groups (LWGs) in simplifying alignments as well as in transferring syntactic dependencies by building an alignment model with LWGs as base units and training a dependency parser on the relations projected using these LWGs. The LWG alignment model using GIZA++ scores decreases the Alignment Error Rate by 1.16 points when compared to the best GIZA++ model trained on lemmas. We also show that a dependency parser trained on the syntactic relations projected using LWGs obtained statistical significant improvements over the relations projected using lemmas by a margin of 3.49%.