{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,31]],"date-time":"2026-03-31T10:23:01Z","timestamp":1774952581509,"version":"3.50.1"},"reference-count":81,"publisher":"Springer Science and Business Media LLC","issue":"2-3","license":[{"start":{"date-parts":[[2020,8,19]],"date-time":"2020-08-19T00:00:00Z","timestamp":1597795200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2020,8,19]],"date-time":"2020-08-19T00:00:00Z","timestamp":1597795200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"funder":[{"DOI":"10.13039\/100010665","name":"H2020 Marie Sklodowska-Curie Actions","doi-asserted-by":"publisher","award":["713567"],"award-info":[{"award-number":["713567"]}],"id":[{"id":"10.13039\/100010665","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Machine Translation"],"published-print":{"date-parts":[[2020,9]]},"DOI":"10.1007\/s10590-020-09251-z","type":"journal-article","created":{"date-parts":[[2020,8,19]],"date-time":"2020-08-19T11:02:41Z","timestamp":1597834961000},"page":"149-195","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":20,"title":["Analysing terminology translation errors in statistical and neural machine translation"],"prefix":"10.1007","volume":"34","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1680-0099","authenticated-orcid":false,"given":"Rejwanul","family":"Haque","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mohammed","family":"Hasanuzzaman","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Andy","family":"Way","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2020,8,19]]},"reference":[{"key":"9251_CR1","unstructured":"Ar\u010dan M, Buitelaar P (2017) Translating domain-specific expressions in knowledge bases with neural machine translation. CoRR. arXiv:1709.02184"},{"issue":"5","key":"9251_CR2","doi-asserted-by":"publisher","first-page":"763","DOI":"10.1017\/S1351324917000195","volume":"23","author":"M Ar\u010dan","year":"2017","unstructured":"Ar\u010dan M, Turchi M, Tonelli S, Buitelaar P (2017) Leveraging bilingual terminology to improve machine translation in a cat environment. Nat Lang Eng 23(5):763\u2013788","journal-title":"Nat Lang Eng"},{"key":"9251_CR3","unstructured":"Ba JL, Kiros JR, Hinton GE (2016) Layer normalization. CoRR. arXiv:1607.06450"},{"key":"9251_CR4","unstructured":"Bahdanau D, Cho K, Bengio Y (2015) Neural machine translation by jointly learning to align and translate. In: 3rd International conference on learning representations (ICLR 2015), San Diego, CA"},{"key":"9251_CR5","doi-asserted-by":"crossref","unstructured":"Bentivogli L, Bisazza A, Cettolo M, Federico M (2016) Neural versus phrase-based machine translation quality: a case study. In: Proceedings of the 2016 conference on empirical methods in natural language processing, pp 257\u2013267, Austin, TX","DOI":"10.18653\/v1\/D16-1025"},{"key":"9251_CR6","unstructured":"Beyer AM, Macketanz V, Burchardt A, Williams P (2017) Can out-of-the-box NMT beat a Domain-trained Moses on Technical Data? In: Proceedings of EAMT user studies and project\/product descriptions, pp 41\u201346, Prague, Czech Republic"},{"key":"9251_CR8","unstructured":"Bojar O, Diatka V, Rychl\u00fd P, Stra\u0148\u00e1k P, Suchomel V, Tamchyna A, Zeman D (2014) HindEnCorp\u2014Hindi-English and Hindi-only corpus for machine translation. In: Proceedings of the ninth international language resources and evaluation conference (LREC\u201914), pp 3550\u20133555, Reykjavik, Iceland"},{"key":"9251_CR7","doi-asserted-by":"crossref","unstructured":"Bojar O, Chatterjee R, Federmann C, Graham Y, Haddow B, Huck M, Jimeno\u00a0Yepes A, Koehn P, Logacheva V, Monz C, Negri M, Neveol A, Neves M, Popel M, Post M, Rubino R, Scarton C, Specia L, Turchi M, Verspoor K, Zampieri M (2016) Findings of the 2016 conference on machine translation. In: Proceedings of the first conference on machine translation, pp 131\u2013198, Berlin, Germany","DOI":"10.18653\/v1\/W16-2301"},{"key":"9251_CR9","doi-asserted-by":"crossref","unstructured":"Bojar O, Federmann C, Fishel M, Graham Y, Haddow B, Huck M, Koehn P, Monz C (2018) Findings of the 2018 conference on machine translation (WMT18). In: Proceedings of the third conference on machine translation, vol. 2: shared task papers, pp 272\u2013307. Association for Computational Linguistics, Belgium, Brussels","DOI":"10.18653\/v1\/W18-6401"},{"issue":"1","key":"9251_CR10","doi-asserted-by":"publisher","first-page":"159","DOI":"10.1515\/pralin-2017-0017","volume":"108","author":"A Burchardt","year":"2017","unstructured":"Burchardt A, Macketanz V, Dehdari J, Heigold G, Peter J-T, Williams P (2017) A linguistic evaluation of rule-based, phrase-based, and neural MT engines. Prague Bull Math Linguist 108(1):159\u2013170","journal-title":"Prague Bull Math Linguist"},{"key":"9251_CR11","unstructured":"Castilho S, Moorkens J, Gaspari F, Sennrich R, Sosoni V, Georgakopoulou P, Lohar P, Way A, Barone AVM, Gialama M (2017) A comparative quality evaluation of PBSMT and NMT using professional translators. In: Proceedings of MT Summit XVI, the 16th machine translation summit, pp 116\u2013131, Nagoya, Japan"},{"key":"9251_CR12","unstructured":"Cettolo M, Niehues J, St\u00fcker S, Bentivogli L, Cattoni R, Federico M (2015) The IWSLT 2015 evaluation campaign. In: Proceedings of the twelfth international workshop on spoken language translation (IWSLT 2015), Da Nang, Vietnam"},{"key":"9251_CR13","doi-asserted-by":"crossref","unstructured":"Chatterjee R, Negri M, Turchi M, Federico M, Specia L, Blain F (2017) Guiding neural machine translation decoding with external knowledge. In: Proceedings of the second conference on machine translation, pp 157\u2013168. Association for Computational Linguistics, Copenhagen, Denmark","DOI":"10.18653\/v1\/W17-4716"},{"key":"9251_CR14","unstructured":"Cherry C, Foster G (2012) Batch tuning strategies for statistical machine translation. In: Proceedings of the 2012 conference of the North American Chapter of the Association for Computational Linguistics: human language technologies, pp 427\u2013436, Montr\u00e9al, Canada"},{"key":"9251_CR15","doi-asserted-by":"crossref","unstructured":"Cho K, van Merri\u00ebnboer B, G\u00fcl\u00e7ehre \u00c7, Bougares F, Schwenk H, Bengio Y (2014) Learning phrase representations using RNN encoder\u2013decoder for statistical machine translation. In: Proceedings of the 2014 conference on empirical methods in natural language processing (EMNLP), pp 1724\u20131734, Doha, Qatar","DOI":"10.3115\/v1\/D14-1179"},{"issue":"1","key":"9251_CR16","doi-asserted-by":"publisher","first-page":"37","DOI":"10.1177\/001316446002000104","volume":"20","author":"J Cohen","year":"1960","unstructured":"Cohen J (1960) A coefficient of agreement for nominal scales. Educ Psychol Meas 20(1):37\u201346","journal-title":"Educ Psychol Meas"},{"key":"9251_CR17","unstructured":"Crego J\u00a0M, Kim J, Klein G, Rebollo A, Yang K, Senellart J, Akhanov E, Brunelle P, Coquard A, Deng Y, Enoue S, Geiss C, Johanson J, Khalsa A, Khiari R, Ko B, Kobus C, Lorieux J, Martins L, Nguyen D, Priori A, Riccardi T, Segal N, Servan C, Tiquet C, Wang B, Yang J, Zhang D, Zhou J, Zoldan P (2016) Systran\u2019s pure neural machine translation systems. CoRR. arXiv:1610.05540"},{"key":"9251_CR18","unstructured":"Denkowski M, Lavie A (2011) Meteor 1.3: automatic metric for reliable optimization and evaluation of machine translation systems. In: Proceedings of the sixth workshop on statistical machine translation, pp 85\u201391, Edinburgh, Scotland"},{"key":"9251_CR19","unstructured":"Durrani N, Schmid H, Fraser A (2011) A joint sequence translation model with integrated reordering. In: Proceedings of the 49th annual meeting of the association for computational linguistics: human language technologies, pp 1045\u20131054, Portland, Oregon, USA"},{"key":"9251_CR21","doi-asserted-by":"crossref","unstructured":"Farajian MA, Turchi M, Negri M, Bertoldi N, Federico M (2017) Neural vs. phrase-based machine translation in a multi-domain scenario. In: Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 2, Short Papers, pages 280\u2013284, Valencia, Spain","DOI":"10.18653\/v1\/E17-2045"},{"key":"9251_CR20","unstructured":"Farajian MA, Bertoldi N, Negri M, Turchi M, Federico M (2018) Evaluation of terminology translation in instance-based neural MT adaptation. In: Proceedings of the 21st Annual conference of the european association for machine translation, pp 149\u2013158, Alicante, Spain"},{"issue":"2","key":"9251_CR22","first-page":"23","volume":"12","author":"P Gage","year":"1994","unstructured":"Gage P (1994) A new algorithm for data compression. C Users J 12(2):23\u201338","journal-title":"C Users J"},{"key":"9251_CR23","unstructured":"Gal Y, Ghahramani Z (2016) A theoretically grounded application of dropout in recurrent neural networks. CoRR. arXiv:1512.05287"},{"key":"9251_CR27","doi-asserted-by":"crossref","unstructured":"Haque R, Penkale S, Way A (2014) Bilingual termbank creation via log-likelihood comparison and phrase-based statistical machine translation. In: Proceedings of the 4th international workshop on computational terminology (Computerm), pp 42\u201351, Dublin, Ireland","DOI":"10.3115\/v1\/W14-4806"},{"issue":"2","key":"9251_CR28","doi-asserted-by":"publisher","first-page":"365","DOI":"10.1007\/s10579-018-9412-4","volume":"52","author":"R Haque","year":"2018","unstructured":"Haque R, Penkale S, Way A (2018) TermFinder: log-likelihood comparison and phrase-based statistical machine translation models for bilingual terminology extraction. Lang Resour Eval 52(2):365\u2013400","journal-title":"Lang Resour Eval"},{"key":"9251_CR24","doi-asserted-by":"crossref","unstructured":"Haque R, Hasanuzzaman M, Way A (2019a) Investigating terminology translation in statistical and neural machine translation: a case study on English-to-Hindi and Hindi-to-English. In: Proceedings of RANLP 2019: recent advances in natural language processing, pp 437\u2013446, Varna, Bulgaria","DOI":"10.26615\/978-954-452-056-4_052"},{"key":"9251_CR25","unstructured":"Haque R, Hasanuzzaman M, Way A (2019b) TermEval: an automatic metric for evaluating terminology translation in MT. In: Proceedings of CICLing 2019, the 20th international conference on computational linguistics and intelligent text processing, La Rochelle, France"},{"issue":"9","key":"9251_CR26","doi-asserted-by":"publisher","first-page":"273","DOI":"10.3390\/info10090273","volume":"10","author":"R Haque","year":"2019","unstructured":"Haque R, Hasanuzzaman M, Way A (2019c) Terminology translation in low-resource scenarios. Information 10(9):273","journal-title":"Information"},{"key":"9251_CR29","doi-asserted-by":"crossref","unstructured":"Hasler E, Gispert A, Iglesias G, Byrne B (2018) Neural machine translation decoding with terminology constraints. In: Proceedings of the 2018 conference of the North American chapter of the Association for Computational Linguistics: Human Language Technologies, vol. 2 (short papers), pp 506\u2013512. Association for Computational Linguistics, New Orleans, LA","DOI":"10.18653\/v1\/N18-2081"},{"key":"9251_CR30","unstructured":"Hassan H, Aue A, Chen C, Chowdhary V, Clark J, Federmann C, Huang X, Junczys-Dowmunt M, Lewis W, Li M, Liu S, Liu T, Luo R, Menezes A, Qin T, Seide F, Tan X, Tian F, Wu L, Wu S, Xia Y, Zhang D, Zhang Z, Zhou M (2018) Achieving human parity on automatic Chinese to English news translation. CoRR. arXiv:1803.05567"},{"key":"9251_CR31","doi-asserted-by":"crossref","unstructured":"He K, Zhang X, Ren S, Sun J (2015) Deep residual learning for image recognition. CoRR. arXiv:1512.03385","DOI":"10.1109\/CVPR.2016.90"},{"key":"9251_CR32","unstructured":"Heafield K, Pouzyrevsky I, Clark JH, Koehn P (2013) Scalable modified Kneser\u2013Ney language model estimation. In: Proceedings of the 51st annual meeting of the Association for Computational Linguistics (vol. 2: short papers), pp 690\u2013696, Sofia, Bulgaria"},{"key":"9251_CR33","doi-asserted-by":"crossref","unstructured":"Hokamp C, Liu Q (2017) Lexically constrained decoding for sequence generation using grid beam search. In: Proceedings of the 55th annual meeting of the Association for Computational Linguistics (vol. 1: long papers), pp 1535\u20131546, Vancouver, BC","DOI":"10.18653\/v1\/P17-1141"},{"key":"9251_CR34","doi-asserted-by":"crossref","unstructured":"Huang G, Zhang J, Zhou Y, Zong C (2016) A simple, straightforward and effective model for joint bilingual terms detection and word alignment in SMT. In: Natural language understanding and intelligent applications, ICCPOL\/NLPCC 2016, vol 10102, pp 103\u2013115","DOI":"10.1007\/978-3-319-50496-4_9"},{"key":"9251_CR35","unstructured":"Huang L, Chiang D (2007) Forest rescoring: faster decoding with integrated language models. In: Proceedings of the 45th annual meeting of the Association of Computational Linguistics, pp 144\u2013151, Prague, Czech Republic"},{"key":"9251_CR36","doi-asserted-by":"crossref","unstructured":"Isabelle P, Cherry C, Foster GF (2017) A challenge set approach to evaluating machine translation. CoRR. arXiv:1704.07431","DOI":"10.18653\/v1\/D17-1263"},{"key":"9251_CR37","unstructured":"James F (2000) Modified Kneser-Ney smoothing of n-gram models. Tech. Rep. 00.07. Research Institute for Advanced Computer Science"},{"key":"9251_CR38","unstructured":"Junczys-Dowmunt M, Dwojak T, Hoang H (2016) Is neural machine translation ready for deployment? A case study on 30 translation directions. CoRR. arXiv:1610.01108"},{"key":"9251_CR39","doi-asserted-by":"crossref","unstructured":"Junczys-Dowmunt M, Grundkiewicz R, Dwojak T, Hoang H, Heafield K, Neckermann T, Seide F, Germann U, Fikri\u00a0Aji A, Bogoychev N, Martins AFT, Birch A (2018) Marian: Fast neural machine translation in C++. In: Proceedings of ACL 2018, system demonstrations, pp 116\u2013121. Association for Computational Linguistics, Melbourne, Australia","DOI":"10.18653\/v1\/P18-4020"},{"key":"9251_CR40","unstructured":"Kalchbrenner N, Blunsom P (2013) Recurrent continuous translation models. In: Proceedings of the 2013 conference on empirical methods in natural language processing (EMNLP), pp 1700\u20131709, Seattle, WA"},{"key":"9251_CR41","unstructured":"Kingma DP, Ba J (2014) Adam: a method for stochastic optimization. CoRR. arXiv:1412.6980"},{"key":"9251_CR42","unstructured":"Kinoshita S, Oshio T, Mitsuhashi T (2017) Comparison of SMT and NMT trained with large patent corpora: Japio at WAT2017. In: Proceedings of the 4th workshop on Asian translation (WAT2017), pp 140\u2013145. Asian Federation of Natural Language Processing"},{"key":"9251_CR43","doi-asserted-by":"crossref","unstructured":"Klubi\u010dka F, Toral A, S\u00e1nchez-Cartagena VM (2017) Fine-grained human evaluation of neural versus phrase-based machine translation.CoRR, arXiv:1706.04389","DOI":"10.1515\/pralin-2017-0014"},{"key":"9251_CR44","doi-asserted-by":"crossref","unstructured":"Klubi\u010dka F, Toral A, S\u00e1nchez-Cartagena VM (2018) Quantitative fine-grained human evaluation of machine translation systems: a case study on English to Croatian. CoRR. arXiv:1802.01451","DOI":"10.1007\/s10590-018-9214-x"},{"key":"9251_CR45","unstructured":"Koehn P (2004) Statistical significance tests for machine translation evaluation. In: Lin D, Wu D (eds) Proceedings of the 2004 conference on empirical methods in natural language processing (EMNLP), pp 388\u2013395, Barcelona, Spain"},{"key":"9251_CR46","unstructured":"Koehn P (2005) Europarl: a parallel corpus for statistical machine translation. In: Proceedings of MT Summit X: the tenth machine translation summit, pp 79\u201386, Phuket, Thailand"},{"key":"9251_CR48","doi-asserted-by":"crossref","unstructured":"Koehn P, Knowles R (2017) Six challenges for neural machine translation. CoRR. arXiv:1706.03872","DOI":"10.18653\/v1\/W17-3204"},{"key":"9251_CR49","doi-asserted-by":"crossref","unstructured":"Koehn P, Och FJ, Marcu D (2003) Statistical phrase-based translation. In: HLT-NAACL 2003: conference combining Human Language Technology conference series and the North American Chapter of the Association for Computational Linguistics conference series, Edmonton, AB, pp 48\u201354","DOI":"10.3115\/1073445.1073462"},{"key":"9251_CR47","doi-asserted-by":"crossref","unstructured":"Koehn P, Hoang H, Birch A, Callison-Burch C, Federico M, Bertoldi N, Cowan B, Shen W, Moran C, Zens R, Dyer C, Bojar O, Constantin A, College W, Herbst E (2007) Moses: Open source toolkit for statistical machine translation. In: ACL 2007, proceedings of the interactive poster and demonstration sessions, pp 177\u2013180, Prague, Czech Republic","DOI":"10.3115\/1557769.1557821"},{"key":"9251_CR50","first-page":"02855","volume":"1710","author":"A Kunchukuttan","year":"2017","unstructured":"Kunchukuttan A, Mehta P, Bhattacharyya P (2017) The IIT Bombay English-Hindi parallel corpus. CoRR 1710:02855","journal-title":"CoRR"},{"key":"9251_CR51","doi-asserted-by":"crossref","unstructured":"Lommel AR, Uszkoreit H, Burchardt A (2014) Multidimensional Quality Metrics (MQM): a framework for declaring and describing translation quality metrics. Tradum\u00e1tica: tecnologies de la traducci\u00f3 (12):455\u2013463","DOI":"10.5565\/rev\/tradumatica.77"},{"key":"9251_CR52","unstructured":"Long Z, Utsuro T, Mitsuhashi T, Yamamoto M (2016) Translation of patent sentences with a large vocabulary of technical terms using neural machine translation. In: Proceedings of the 3rd workshop on Asian translation (WAT2016), pp 47\u201357, Osaka, Japan"},{"issue":"2","key":"9251_CR53","first-page":"28","volume":"17","author":"V Macketanz","year":"2017","unstructured":"Macketanz V, Avramidis E, Burchardt A, Helcl J, Srivastava A (2017) Machine translation: phrase-based, rule-based and neural approaches with linguistic evaluation. Cybern Inf Technol 17(2):28\u201343","journal-title":"Cybern Inf Technol"},{"key":"9251_CR54","volume-title":"Anaphora resolution","author":"R Mitkov","year":"2002","unstructured":"Mitkov R (2002) Anaphora resolution. Longman, Harlow"},{"issue":"1","key":"9251_CR55","doi-asserted-by":"publisher","first-page":"19","DOI":"10.1162\/089120103321337421","volume":"29","author":"FJ Och","year":"2003","unstructured":"Och FJ, Ney H (2003) A systematic comparison of various statistical alignment models. Comput Linguist 29(1):19\u201351","journal-title":"Comput Linguist"},{"key":"9251_CR56","doi-asserted-by":"crossref","unstructured":"Papineni K, Roukos S, Ward T, Zhu W-J (2002) BLEU: a method for automatic evaluation of machine translation. In: ACL-2002: 40th annual meeting of the Association for Computational Linguistics. ACL, Philadelphia, PA, pp 311\u2013318","DOI":"10.3115\/1073083.1073135"},{"key":"9251_CR57","unstructured":"Pinnis M (2015) Dynamic terminology integration methods in statistical machine translation. In: Proceedings of the 18th annual conference of the European Association for Machine Translation (EAMT 2015), pp 89\u201396, Antalya, Turkey"},{"key":"9251_CR58","unstructured":"Pinnis M, Ljube\u0161i\u0107 N, \u015etef\u0103nescu D, Skadi\u0146a I, Tadi\u0107 M, Gornostay T (2012) Term extraction, tagging, and mapping tools for under-resourced languages. In: Proceedings of the 10th conference on terminology and knowledge engineering (TKE 2012), pp 193\u2013208, Madrid, Spain"},{"issue":"1","key":"9251_CR59","doi-asserted-by":"publisher","first-page":"209","DOI":"10.1515\/pralin-2017-0021","volume":"108","author":"M Popovi\u0107","year":"2017","unstructured":"Popovi\u0107 M (2017) Comparing language related issues for NMT and pbmt between German and English. Prague Bull Math Linguist 108(1):209\u2013220","journal-title":"Prague Bull Math Linguist"},{"issue":"4","key":"9251_CR60","doi-asserted-by":"publisher","first-page":"657","DOI":"10.1162\/COLI_a_00072","volume":"37","author":"M Popovi\u0107","year":"2011","unstructured":"Popovi\u0107 M, Ney H (2011) Towards automatic error analysis of machine translation output. Comput Linguist 37(4):657\u2013688","journal-title":"Comput Linguist"},{"key":"9251_CR61","doi-asserted-by":"crossref","unstructured":"Post M, Vilar D (2018) Fast lexically constrained decoding with dynamic beam allocation for neural machine translation. In: Proceedings of the 2018 conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, vol 1 (long papers), pp 1314\u20131324, New Orleans, LO","DOI":"10.18653\/v1\/N18-1119"},{"key":"9251_CR62","doi-asserted-by":"crossref","unstructured":"Press O, Wolf L (2016) Using the output embedding to improve language models. CoRR. arXiv:1608.05859","DOI":"10.18653\/v1\/E17-2025"},{"key":"9251_CR63","doi-asserted-by":"publisher","first-page":"385","DOI":"10.1007\/s10579-019-09453-9","volume":"54","author":"A Rigouts Terryn","year":"2019","unstructured":"Rigouts Terryn A, Hoste V, Lefever E (2019) In no uncertain terms: a dataset for monolingual and multilingual automatic term extraction from comparable corpora. Lang Resour Eval 54:385\u2013418","journal-title":"Lang Resour Eval"},{"key":"9251_CR64","doi-asserted-by":"crossref","unstructured":"Sennrich R, Haddow B, Birch A (2015) Improving neural machine translation models with monolingual data. CoRR. arXiv:1511.06709","DOI":"10.18653\/v1\/P16-1009"},{"key":"9251_CR65","doi-asserted-by":"crossref","unstructured":"Sennrich R, Haddow B, Birch A (2016a) Edinburgh neural machine translation systems for WMT 16. In: Proceedings of the first conference on machine translation, pp 371\u2013376, Berlin, Germany","DOI":"10.18653\/v1\/W16-2323"},{"key":"9251_CR66","doi-asserted-by":"crossref","unstructured":"Sennrich R, Haddow B, Birch A (2016b) Neural machine translation of rare words with subword units. In: Proceedings of the 54th annual meeting of the Association for Computational Linguistics (volume 1: long papers), pp 1715\u20131725, Berlin, Germany","DOI":"10.18653\/v1\/P16-1162"},{"key":"9251_CR67","unstructured":"Shterionov D, Nagle P, Casanellas L, Superbo R, O\u2019Dowd T (2017) Empirical evaluation of nmt and pbsmt quality for large-scale translation production. In: User track of the 20th annual conference of the European Association for Machine Translation (EAMT), pp 74\u201379, Czech Republic, Prague"},{"key":"9251_CR68","unstructured":"Skadi\u0146\u0161 R, Puri\u0146\u0161 M, Skadi\u0146a I, Vasil\u0327jevs A (2011) Evaluation of SMT in localization to under-resourced inflected language. In: Proceedings of the 15th international conference of the European Association for Machine Translation (EAMT 2011), pp 35\u201340, Leuven, Belgium"},{"key":"9251_CR69","unstructured":"Snover M, Dorr B, Schwartz R, Micciulla L, Makhoul J (2006) A study of translation edit rate with targeted human annotation. In: In Proceedings of the 7th biennial conference of the Association for Machine Translation in the Americas (AMTA-2006), pp 223\u2013231, Cambridge, MA"},{"key":"9251_CR70","unstructured":"Specia L, Harris K, Blain F, Burchardt A, Macketanz V, Skadi\u0146a I, Negri M, Turchi M (2017) Translation quality and productivity: a study on rich morphology languages. In: Proceedings of MT summit XVI, the 16th machine translation summit, pp 55\u201371, Nagoya, Japan"},{"key":"9251_CR71","unstructured":"Sutskever I, Vinyals O, Le QV (2014) Sequence to sequence learning with neural networks. In: Proceedings of the 27th international conference on neural information processing systems, NIPS\u201914, pp 3104\u20133112, Montreal, Canada"},{"key":"9251_CR72","unstructured":"Tiedemann J (2012) Parallel data, tools and interfaces in OPUS. In: Proceedings of the 8th international conference on language resources and evaluation (LREC\u20192012), pp 2214\u20132218, Istanbul, Turkey"},{"key":"9251_CR73","doi-asserted-by":"crossref","unstructured":"Toral A, S\u00e1nchez-Cartagena VM (2017) A multifaceted evaluation of neural versus phrase-based machine translation for 9 language directions. CoRR. arXiv:1701.02901","DOI":"10.18653\/v1\/E17-1100"},{"key":"9251_CR74","doi-asserted-by":"crossref","unstructured":"Toral A, Way A (2018) What level of quality can neural machine translation attain on literary text? In: Translation quality assessment. Springer, Cham, pp 263\u2013287","DOI":"10.1007\/978-3-319-91241-7_12"},{"key":"9251_CR75","unstructured":"Vaswani A, Shazeer N, Parmar N, Uszkoreit J, Jones L, Gomez AN, Kaiser L, Polosukhin I (2017) Attention is all you need. CoRR. arXiv:1706.03762"},{"key":"9251_CR76","unstructured":"Vaswani A, Zhao Y, Fossum V, Chiang D (2013) Decoding with large-scale neural language models improves translation. In: Proceedings of the 2013 conference on empirical methods in natural language processing, pp 1387\u20131392, Seattle, Washington, USA"},{"key":"9251_CR77","unstructured":"Vintar \u0160 (2018) Terminology translation accuracy in statistical versus neural mt: An evaluation for the English\u2013Slovene language pair. In: Du J, Ar\u010dan M, Liu Q, Isahara H (eds) Proceedings of the LREC 2018 workshop MLP\u2013MomenT: the second workshop on multi-language processing in a globalising world and the first workshop on multilingualism at the intersection of knowledge bases and machine translation, pp 34\u201337, Miyazaki, Japan. European Language Resources Association (ELRA), Paris"},{"key":"9251_CR78","doi-asserted-by":"crossref","unstructured":"Way A (2018) Quality expectations of machine translation. In: Translation quality assessment: from principles to practice. Springer, Cham","DOI":"10.1007\/978-3-319-91241-7_8"},{"key":"9251_CR79","unstructured":"Wu Y, Schuster M, Chen Z, Le Q\u00a0V, Norouzi M, Macherey W, Krikun M, Cao Y, Gao Q, Macherey K, Klingner J, Shah A, Johnson M, Liu X, Kaiser L, Gouws S, Kato Y, Kudo T, Kazawa H, Stevens K, Kurian G, Patil N, Wang W, Young C, Smith J, Riesa J, Rudnick A, Vinyals O, Corrado G, Hughes M, Dean J (2016) Google\u2019s neural machine translation system: bridging the gap between human and machine translation. CoRR. arXiv:1609.08144"},{"key":"9251_CR80","doi-asserted-by":"crossref","unstructured":"Yeh A (2000) More accurate tests for the statistical significance of result differences. In: Proceedings of the 18th conference on computational linguistics, vol 2, COLING 2000, pp 947\u2013953, Saarbr\u00fccken, Germany","DOI":"10.3115\/992730.992783"},{"key":"9251_CR81","unstructured":"Ziemski M, Junczys-Dowmunt M, Pouliquen B (2016) The united nations parallel corpus v1.0. In: Proceedings of the tenth international conference on language resources and evaluation (LREC 2016), pp 3530\u20133534, Portoro\u017e, Slovenia"}],"container-title":["Machine Translation"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10590-020-09251-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10590-020-09251-z\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10590-020-09251-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,8,12]],"date-time":"2024-08-12T02:31:28Z","timestamp":1723429888000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10590-020-09251-z"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,8,19]]},"references-count":81,"journal-issue":{"issue":"2-3","published-print":{"date-parts":[[2020,9]]}},"alternative-id":["9251"],"URL":"https:\/\/doi.org\/10.1007\/s10590-020-09251-z","relation":{},"ISSN":["0922-6567","1573-0573"],"issn-type":[{"value":"0922-6567","type":"print"},{"value":"1573-0573","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,8,19]]},"assertion":[{"value":"17 April 2019","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"23 July 2020","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"19 August 2020","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}