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[1] Philipp Koehn,et al. Convergence of Translation Memory and Statistical Machine Translation , 2010, JEC.
[2] Jian Zhang,et al. Experiments in Medical Translation Shared Task at WMT 2014 , 2014, WMT@ACL.
[3] Hermann Ney,et al. Towards Automatic Error Analysis of Machine Translation Output , 2011, CL.
[4] Marco Turchi,et al. The FBK Participation in the WMT15 Automatic Post-editing Shared Task , 2015 .
[5] Philipp Koehn,et al. Further Meta-Evaluation of Machine Translation , 2008, WMT@ACL.
[6] Alon Lavie,et al. METEOR: An Automatic Metric for MT Evaluation with Improved Correlation with Human Judgments , 2005, IEEvaluation@ACL.
[7] Christopher D. Manning,et al. Stanford Neural Machine Translation Systems for Spoken Language Domains , 2015, IWSLT.
[8] Tailor-made quality-controlled translation , 2013, TC.
[9] Yifan He,et al. Improving the Objective Function in Minimum Error Rate Training , 2009, MTSUMMIT.
[10] Andy Way,et al. Comparing Translator Acceptability of TM and SMT Outputs , 2016, EAMT.
[11] Jean Carletta,et al. Proceedings of the ACL Workshop on Intrinsic and Extrinsic Evaluation Measures for Machine Translation and/or Summarization , 2005, ACL 2005.
[12] Andy Way,et al. Declarative Evaluation of an MT system: Practical Experiences , 1991 .
[13] Ding Liu,et al. Syntactic Features for Evaluation of Machine Translation , 2005, IEEvaluation@ACL.
[14] Matthew G. Snover,et al. A Study of Translation Edit Rate with Targeted Human Annotation , 2006, AMTA.
[15] Alon Lavie,et al. Meteor, M-BLEU and M-TER: Evaluation Metrics for High-Correlation with Human Rankings of Machine Translation Output , 2008, WMT@ACL.
[16] John S. White,et al. Task-Based Evaluation for Machine Translation , 1999 .
[17] Stefan Riezler,et al. On Some Pitfalls in Automatic Evaluation and Significance Testing for MT , 2005, IEEvaluation@ACL.
[18] Alexandra Birch,et al. The Edinburgh Machine Translation Systems for IWSLT 2015 , 2015 .
[19] Dragos Stefan Munteanu,et al. ParaEval: Using Paraphrases to Evaluate Summaries Automatically , 2006, NAACL.
[20] Nadira Hofmann. MT-enhanced fuzzy matching with Transit NXT and STAR Moses , 2015, EAMT.
[21] Vladimir I. Levenshtein,et al. Binary codes capable of correcting deletions, insertions, and reversals , 1965 .
[22] Philipp Koehn,et al. Moses: Open Source Toolkit for Statistical Machine Translation , 2007, ACL.
[23] Chin-Yew Lin,et al. ORANGE: a Method for Evaluating Automatic Evaluation Metrics for Machine Translation , 2004, COLING.
[24] Jörg Tiedemann,et al. Climbing Mont BLEU: The Strange World of Reachable High-BLEU Translations , 2016, EAMT.
[25] Ralph Weischedel,et al. A STUDY OF TRANSLATION ERROR RATE WITH TARGETED HUMAN ANNOTATION , 2005 .
[26] Alon Lavie,et al. A framework for interactive and automatic refinement of transfer-based machine translation , 2005, EAMT.
[27] Salim Roukos,et al. Bleu: a Method for Automatic Evaluation of Machine Translation , 2002, ACL.
[28] Marta R. Costa-jussà,et al. Study and correlation analysis of linguistic, perceptual, and automatic machine translation evaluations , 2012, J. Assoc. Inf. Sci. Technol..
[29] Khalil Sima'an,et al. ILLC-UvA Adaptation System (Scorpio) at WMT’16 IT-DOMAIN Task , 2016, WMT.
[30] George R. Doddington,et al. Automatic Evaluation of Machine Translation Quality Using N-gram Co-Occurrence Statistics , 2002 .
[31] Lorna Balkan,et al. Test Suites for Natural Language Processing , 1995, TC.
[32] Maja Popovic,et al. chrF: character n-gram F-score for automatic MT evaluation , 2015, WMT@EMNLP.
[33] Stefan Riezler,et al. The Heidelberg University English-German translation system for IWSLT 2015 , 2015, IWSLT.
[34] Ming Zhou,et al. Sentence Level Machine Translation Evaluation as a Ranking , 2007, WMT@ACL.
[35] Philipp Koehn,et al. Re-evaluating the Role of Bleu in Machine Translation Research , 2006, EACL.
[36] Daniel Marcu,et al. Statistical Phrase-Based Translation , 2003, NAACL.
[37] Luciana Graziuso,et al. Is That a Fish In Your Ear? ─ Translation and the Meaning of Everything , 2012 .
[38] Andy Way,et al. Labelled Dependencies in Machine Translation Evaluation , 2007, WMT@ACL.
[39] Margaret King,et al. Using Test Suites in Evaluation of Machine Translation Systems , 1990, COLING.
[40] Rebecca Hwa,et al. Regression for Sentence-Level MT Evaluation with Pseudo References , 2007, ACL.
[41] John R. Pierce,et al. Language and Machines: Computers in Translation and Linguistics , 1966 .
[42] Andy Way. Machine translation: Where are we at today? , 2020 .
[43] Rico Sennrich,et al. Improving Neural Machine Translation Models with Monolingual Data , 2015, ACL.
[44] Marc Dymetman,et al. Dynamic Translation Memory: Using Statistical Machine Translation to Improve Translation Memory Fuzzy Matches , 2008, CICLing.
[45] Dragos Ciobanu,et al. Traditional and Emerging Use-Cases for Machine Translation , 2013 .
[46] Doug Arnold,et al. Machine Translation: An Introductory Guide , 1994 .
[47] Qun Liu,et al. A discriminative framework of integrating translation memory features into SMT , 2014, AMTA.
[48] Hermann Ney,et al. Error Analysis of Statistical Machine Translation Output , 2006, LREC.
[49] David Bellos,et al. Is That a Fish in Your Ear?: Translation and the Meaning of Everything , 2011 .
[50] Louisa Sadler,et al. Automatic Test Suite generation , 2004, Machine Translation.
[51] Kevin Duh,et al. Automatic Evaluation of Translation Quality for Distant Language Pairs , 2010, EMNLP.
[52] Christopher D. Manning,et al. Achieving Open Vocabulary Neural Machine Translation with Hybrid Word-Character Models , 2016, ACL.
[53] Deborah A. Coughlin,et al. Correlating automated and human assessments of machine translation quality , 2003, MTSUMMIT.
[54] Ben Taskar,et al. An End-to-End Discriminative Approach to Machine Translation , 2006, ACL.
[55] P. Isabelle,et al. Phrase-based Machine Translation in a Computer-assisted Translation Environment , 2009, MTSUMMIT.
[56] Yifan He,et al. Consistent Translation using Discriminative Learning - A Translation Memory-inspired Approach , 2011, ACL.
[57] Yoshua Bengio,et al. A Character-level Decoder without Explicit Segmentation for Neural Machine Translation , 2016, ACL.
[58] Franz Josef Och,et al. Minimum Error Rate Training in Statistical Machine Translation , 2003, ACL.
[59] Yifan He,et al. Learning Labelled Dependencies in Machine Translation Evaluation , 2009, EAMT.
[60] Kavita Thomas. Designing a Task-Based Evaluation Methodology for a Spoken Machine Translation System , 1999, ACL.
[61] Dimitar Shterionov,et al. Human versus automatic quality evaluation of NMT and PBSMT , 2018, Machine Translation.
[62] Chengqing Zong,et al. Integrating Translation Memory into Phrase-Based Machine Translation during Decoding , 2013, ACL.
[63] Josef van Genabith,et al. Integrating N-best SMT Outputs into a TM System , 2010, COLING.
[64] Bogdan Babych,et al. Extending the BLEU MT Evaluation Method with Frequency Weightings , 2004, ACL.
[65] Giselle de Almeida,et al. Translating the post-editor: an investigation of post-editing changes and correlations with professional experience across two Romance languages , 2013 .
[66] Yifan He,et al. Bridging SMT and TM with Translation Recommendation , 2010, ACL.
[67] Andy Way. David Bellos (ed): Is that a fish in your ear: translation and the meaning of everything , 2012, Machine Translation.
[68] Arianna Bisazza,et al. Neural versus Phrase-Based Machine Translation Quality: a Case Study , 2016, EMNLP.
[69] Jan Niehues,et al. The KIT translation systems for IWSLT 2015 , 2015, IWSLT.
[70] George A. Miller,et al. Introduction to WordNet: An On-line Lexical Database , 1990 .
[71] Yoshua Bengio,et al. Montreal Neural Machine Translation Systems for WMT’15 , 2015, WMT@EMNLP.
[72] Andy Way,et al. A Framework for Diagnostic Evaluation of MT Based on Linguistic Checkpoints , 2011, MTSUMMIT.
[73] Clare R. Voss,et al. Task-based Evaluation of Machine Translation (MT) Engines. Measuring How Well People Extract Who, When, Where-Type Elements in MT Output , 2006, EAMT.
[74] Hermann Ney,et al. Accelerated DP based search for statistical translation , 1997, EUROSPEECH.
[75] Harold L. Somers,et al. Round-trip Translation: What Is It Good For? , 2005, ALTA.
[76] William Lewis,et al. Controlled Ascent: Imbuing Statistical MT with Linguistic Knowledge , 2013, HyTra@ACL.
[77] Rico Sennrich,et al. Edinburgh Neural Machine Translation Systems for WMT 16 , 2016, WMT.
[78] Yifan He,et al. Metric and reference factors in minimum error rate training , 2010, Machine Translation.