BLEU: a method for automatic evaluation of machine translation
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Paraphrasing with bilingual parallel corpora
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Creating speech and language data with Amazon's Mechanical Turk
CSLDAMT '10 Proceedings of the NAACL HLT 2010 Workshop on Creating Speech and Language Data with Amazon's Mechanical Turk
Collecting highly parallel data for paraphrase evaluation
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1
Generating targeted paraphrases for improved translation
ACM Transactions on Intelligent Systems and Technology (TIST) - Special Sections on Paraphrasing; Intelligent Systems for Socially Aware Computing; Social Computing, Behavioral-Cultural Modeling, and Prediction
Paraphrase acquisition via crowdsourcing and machine learning
ACM Transactions on Intelligent Systems and Technology (TIST) - Special Sections on Paraphrasing; Intelligent Systems for Socially Aware Computing; Social Computing, Behavioral-Cultural Modeling, and Prediction
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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.