Turker-Assisted Paraphrasing for English-Arabic Machine Translation

Michael J. Denkowski, Hassan Al-Haj, Alon Lavie

Abstract: This paper describes a semi-automatic paraphrasing task for English-Arabic machine translation conducted using Amazon Mechanical Turk. The method for automatically extracting paraphrases is described, as are several human judgment tasks completed by Turkers. An ideal task type, revised specifically to address feedback from Turkers, is shown to be sophisticated enough to identify and filter problem Turkers while remaining simple enough for non-experts to complete. The results of this task are discussed along with the viability of using this data to combat data sparsity in MT.