Building English-to-Serbian Machine Translation System for IMDb Movie Reviews
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Andy Way | Pintu Lohar | Maja Popović | Maja Popovic | Andy Way | Pintu Lohar | P. Lohar
[1] Maja Popovic,et al. Language-related issues for NMT and PBMT for English–German and English–Serbian , 2018, Machine Translation.
[2] François Yvon,et al. Using Monolingual Data in Neural Machine Translation: a Systematic Study , 2018, WMT.
[3] Arkaitz Zubiaga,et al. TweetMT: A Parallel Microblog Corpus , 2016, LREC.
[4] Alexander M. Rush,et al. OpenNMT: Open-Source Toolkit for Neural Machine Translation , 2017, ACL.
[5] Andy Way,et al. Balancing Translation Quality and Sentiment Preservation (Non-archival Extended Abstract) , 2018, AMTA.
[6] Alon Lavie,et al. The Meteor metric for automatic evaluation of machine translation , 2009, Machine Translation.
[7] Stefan Riezler,et al. Twitter Translation using Translation-Based Cross-Lingual Retrieval , 2012, WMT@NAACL-HLT.
[8] Tomaz Erjavec,et al. Adapting a State-of-the-Art Tagger for South Slavic Languages to Non-Standard Text , 2017, BSNLP@EACL.
[9] Jennifer Foster,et al. Estimating the Quality of Translated User-Generated Content , 2013, IJCNLP.
[10] Alexandra Balahur,et al. Multilingual Sentiment Analysis using Machine Translation? , 2012, WASSA@ACL.
[11] Rico Sennrich,et al. Improving Neural Machine Translation Models with Monolingual Data , 2015, ACL.
[12] Andy Way,et al. Investigating Backtranslation in Neural Machine Translation , 2018, EAMT.
[13] Philipp Koehn,et al. Six Challenges for Neural Machine Translation , 2017, NMT@ACL.
[14] Maja Popovic. Hjerson: An Open Source Tool for Automatic Error Classification of Machine Translation Output , 2011, Prague Bull. Math. Linguistics.
[15] Jan Snajder,et al. Comparison of Short-Text Sentiment Analysis Methods for Croatian , 2017, BSNLP@EACL.
[16] Christopher Potts,et al. Learning Word Vectors for Sentiment Analysis , 2011, ACL.
[17] Mihael Arcan,et al. Identifying main obstacles for statistical machine translation of morphologically rich South Slavic languages , 2015, EAMT.
[18] Maja Popovic,et al. chrF: character n-gram F-score for automatic MT evaluation , 2015, WMT@EMNLP.
[19] Maja Popović,et al. Exploring cross-language statistical machine translation for closely related South Slavic languages , 2014, EMNLP 2014.
[20] Antonio Toral,et al. A Multifaceted Evaluation of Neural versus Phrase-Based Machine Translation for 9 Language Directions , 2017, EACL.
[21] Hermann Ney,et al. CharacTer: Translation Edit Rate on Character Level , 2016, WMT.
[22] Alexandru Ceausu,et al. South-East European Times : A parallel corpus of Balkan languages , Francis Tyers and , 2010 .
[23] Andy Way,et al. Domain Adaptation in SMT of User-Generated Forum Content Guided by OOV Word Reduction: Normalization and/or Supplementary Data , 2012, EAMT.
[24] Alexandra Balahur,et al. Comparative experiments using supervised learning and machine translation for multilingual sentiment analysis , 2014, Comput. Speech Lang..
[25] Andy Way,et al. Maintaining Sentiment Polarity in Translation of User-Generated Content , 2017, Prague Bull. Math. Linguistics.
[26] Salim Roukos,et al. Bleu: a Method for Automatic Evaluation of Machine Translation , 2002, ACL.
[27] Janez Brest,et al. Slavic languages in phrase-based statistical machine translation: a survey , 2017, Artificial Intelligence Review.
[28] Matthew G. Snover,et al. A Study of Translation Edit Rate with Targeted Human Annotation , 2006, AMTA.
[29] Wang Ling,et al. Microblogs as Parallel Corpora , 2013, ACL.
[30] Jaehong Park,et al. Building a Neural Machine Translation System Using Only Synthetic Parallel Data , 2017, ArXiv.