Application of Pronominal Divergence and Anaphora Resolution in English-Hindi Machine Translation

Abstract

So far the majority of Machine Translation (MT) research has focused on translation at the level of individual sentences. For sentence level translation, Machine Translation has addressed various divergence issues for large variety of languages; the issue of pronominal divergence has been presented only recently. Since the quality of translation as required by users follows coherent multi-sentence discourse structure in a specific context, the pronominal divergence helps us in understanding the nuances of translation arising out of disparity in the languages. Subsequently using clues from this divergence, the anaphora resolution system can find the correct interpretation for the given pronominal referents and other entities by resolving the inter-sentential context. In the literature, researchers have examined the issue and have proposed ways for their classification and resolution of anaphora. However for Indic languages, not many studies are available. In this paper, we discuss different aspects of pronominal divergence that affects the anaphora resolution in English Hindi Machine Translation (EHMT). The study shall be helpful in developing approaches that can explicitly use inter-sentential information in order to resolve specific types of ambiguity and which can generate coherent multi-sentence discourse structure in the target language to produce higher quality of translation Machine Translation.