Towards improving machine translation using user generated content

Abstract

This paper presents a novel approach to overcome the limitation inherited in statistical machine translation services where the translation of new terms is not covered. The proposed approach is based on the power of user generated content to drive Arabic translations of English words. Our initial pilot experiment reveals the potential of our approach. This approach can act as an add-on to improve the quality of existing statistical translation services such as Google Translate.