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Joshua 2.0: A Toolkit for Parsing-Based Machine Translation with Syntax, Semirings, Discriminative Training and Other Goodies., , , , , , , , , and 1 other author(s). WMT@ACL, page 133-137. Association for Computational Linguistics, (2010)Joshua: An Open Source Toolkit for Parsing-Based Machine Translation., , , , , , , and . WMT@EACL, page 135-139. Association for Computational Linguistics, (2009)Evaluating (and Improving) Sentence Alignment under Noisy Conditions., and . WMT@ACL, page 484-493. The Association for Computer Linguistics, (2013)Modeling Annotators: A Generative Approach to Learning from Annotator Rationales., and . EMNLP, page 31-40. ACL, (2008)Crowdsourcing Translation: Professional Quality from Non-Professionals., and . ACL, page 1220-1229. The Association for Computer Linguistics, (2011)The Arabic Online Commentary Dataset: an Annotated Dataset of Informal Arabic with High Dialectal Content., and . ACL (2), page 37-41. The Association for Computer Linguistics, (2011)Findings of the 2011 Workshop on Statistical Machine Translation., , , and . WMT@EMNLP, page 22-64. Association for Computational Linguistics, (2011)Feasibility of Human-in-the-loop Minimum Error Rate Training., and . EMNLP, page 52-61. ACL, (2009)Z-MERT: A Fully Configurable Open Source Tool for Minimum Error Rate Training of Machine Translation Systems.. Prague Bull. Math. Linguistics, (2009)Predicting Human-Targeted Translation Edit Rate via Untrained Human Annotators., and . HLT-NAACL, page 369-372. The Association for Computational Linguistics, (2010)