Part of
Computers and Translation: A translator's guideEdited by Harold Somers
[Benjamins Translation Library 35] 2003
► pp. 297–317
Edited by Harold Somers
[Benjamins Translation Library 35] 2003
► pp. 297–317
16. Post-editing
Cited by
Cited by 54 other publications
Aikawa, Takako, Kentaro Yamamoto & Hitoshi Isahara
2012. The Impact of Crowdsourcing Post-editing with the Collaborative Translation Framework. In Advances in Natural Language Processing [Lecture Notes in Computer Science, 7614], ► pp. 1 ff. 
Alcina, Amparo
2008. Translation technologies. Target. International Journal of Translation Studies 20:1 ► pp. 79 ff.
Almanna, Ali & Rafik Jamoussi
2022. NMT verb rendering: A cognitive approach to informing Arabic-into-English post-editing. Open Linguistics 8:1 ► pp. 310 ff.
Anastasiou, Dimitra & Rajat Gupta
2011. Comparison of crowdsourcing translation with Machine Translation. Journal of Information Science 37:6 ► pp. 637 ff.
Bowker, Lynne
2005. What Does It Take to Work in the Translation Profession in Canada in the 21st Century?. Meta 49:4 ► pp. 960 ff.
Bowker, Lynne
2009. Official Language Minority Communities, Machine Translation, and Translator Education: Reflections on the Status Quo and Considerations for the Future. TTR 21:2 ► pp. 15 ff.
Bowker, Lynne & Jairo Buitrago Ciro
2015. Investigating the usefulness of machine translation for newcomers at the public library. Translation and Interpreting Studies 10:2 ► pp. 165 ff.
Castilho, Sheila, Stephen Doherty, Federico Gaspari & Joss Moorkens
2018. Approaches to Human and Machine Translation Quality Assessment. In Translation Quality Assessment [Machine Translation: Technologies and Applications, 1], ► pp. 9 ff.
Corpas Pastor, Gloria & Fernando Sánchez Rodas
2021. Chapter 1. Now what?. In Corpora in Translation and Contrastive Research in the Digital Age [Benjamins Translation Library, 158], ► pp. 23 ff.
Cui, Ying, Xiao Liu & Yuqin Cheng
2023. A Comparative Study on the Effort of Human Translation and Post-Editing in Relation to Text Types: An Eye-Tracking and Key-Logging Experiment. SAGE Open 13:1 ► pp. 215824402311558 ff.
de Jesus Martins, Débora Beatriz & Helena de Medeiros Caseli
2015. Automatic machine translation error identification. Machine Translation 29:1 ► pp. 1 ff.
DEDE, Volkan & Elena ANTONOVA-ÜNLÜ
2022. Does a Formal Post-editing Training Affect the Performance of Novice Post-editors? An Experimental Study. Cankaya University Journal of Humanities and Social Sciences 16:2 ► pp. 131 ff.
Díaz-Millón, Mar, Irene Rivera-Trigueros, María Dolores Olvera-Lobo & Juncal Gutiérrez-Artacho
2020. Disruptive Methodologies and Cross-Curricular Competencies for a Training Adapted to New Professional Profiles. In Enhancing Learning Design for Innovative Teaching in Higher Education [Advances in Higher Education and Professional Development, ], ► pp. 83 ff.
Flanagan, Marian & Tina Paulsen Christensen
2014. Testing post-editing guidelines: how translation trainees interpret them and how to tailor them for translator training purposes. The Interpreter and Translator Trainer 8:2 ► pp. 257 ff.
Forcada, Mikel L.
2010. Machine translation today. In Handbook of Translation Studies [Handbook of Translation Studies, 1], ► pp. 215 ff.
Garcia, Ignacio
2010. Is machine translation ready yet?. Target. International Journal of Translation Studies 22:1 ► pp. 7 ff.
Garcia, Ignacio
2011. Translating by post-editing: is it the way forward?. Machine Translation 25:3 ► pp. 217 ff.
Guo, Yanlin
2020. Prospects for the teaching of translation majors in the new era. Babel. Revue internationale de la traduction / International Journal of Translation 66:4-5 ► pp. 867 ff.
Guo, Yue
2022. Machine Translation in the Teaching and Learning of Chinese as a Foreign Language. In Applying Mobile Technologies to Chinese Language Learning [Advances in Educational Technologies and Instructional Design, ], ► pp. 35 ff.
Gutiérrez-Artacho, Juncal, María-Dolores Olvera-Lobo & Irene Rivera-Trigueros
2019. Hybrid Machine Translation Oriented to Cross-Language Information Retrieval: English-Spanish Error Analysis. In New Knowledge in Information Systems and Technologies [Advances in Intelligent Systems and Computing, 930], ► pp. 185 ff.
High, Michael David
2023. The Perils and Potential Benefits of Machine Translation in Transnational Higher Education. In Handbook of Research on Developments and Future Trends in Transnational Higher Education [Advances in Higher Education and Professional Development, ], ► pp. 115 ff.
Huang, Jie & Jianhua Wang
2023. Post-editing machine translated subtitles: examining the effects of non-verbal input on student translators’ effort. Perspectives 31:4 ► pp. 620 ff.
Jiménez-Crespo, Miguel A.
2017. The role of translation technologies in Spanish language learning. Journal of Spanish Language Teaching 4:2 ► pp. 181 ff.
Jiménez-Crespo, Miguel A.
2017. How much would you like to pay? Reframing and expanding the notion of translation quality through crowdsourcing and volunteer approaches. Perspectives 25:3 ► pp. 478 ff.
Jiménez-Crespo, Miguel A.
2018. Crowdsourcing and Translation Quality: Novel Approaches in the Language Industry and Translation Studies. In Translation Quality Assessment [Machine Translation: Technologies and Applications, 1], ► pp. 69 ff.
Koby, Geoffrey S.
2012. Post‐Editing of Machine Translation. In The Encyclopedia of Applied Linguistics,
Li, Yuting, Xiuying Lu & S.-B. Tsai
2021. Study on Post-editing for Machine Translation of Railway Engineering Texts. SHS Web of Conferences 96 ► pp. 05001 ff.
Li, Zheng & Ming Tao Xia
2013. The Application of Computer-Aided Translation Technology in the Translation Teaching and Research. Applied Mechanics and Materials 422 ► pp. 255 ff.
Mohsen, Mohammed Ali, Sultan Althebi & Mohammed Albahooth
2023. A scientometric study of three decades of machine translation research: Trending issues, hotspot research, and co-citation analysis. Cogent Arts & Humanities 10:1
Moorkens, Joss
2018. Chapter 4. Eye tracking as a measure of cognitive effort for post-editing of machine translation. In Eye Tracking and Multidisciplinary Studies on Translation [Benjamins Translation Library, 143], ► pp. 55 ff.
Munkova, Dasa, Michal Munk, Katarina Welnitzova & Johanna Jakabovicova
2021. Product and Process Analysis of Machine Translation into the Inflectional Language. SAGE Open 11:4 ► pp. 215824402110545 ff.
Munková, Daša, Michal Munk, Ľubomír Benko & Jakub Absolon
2020. From Old Fashioned “One Size Fits All” to Tailor Made Online Training. In The Challenges of the Digital Transformation in Education [Advances in Intelligent Systems and Computing, 916], ► pp. 365 ff.
Niño, Ana
2008. Evaluating the use of machine translation post-editing in the foreign language class. Computer Assisted Language Learning 21:1 ► pp. 29 ff.
O’Brien, Sharon
2005. Methodologies for Measuring the Correlations between Post-Editing Effort and Machine Translatability. Machine Translation 19:1 ► pp. 37 ff.
PEKCOŞKUN GÜNER, Sevda & Edip Serdar GÜNER
2023. Çeviri iş akışında makine çevirisi sistemleri ve sohbet robotlarının bütünleşik kullanımı. RumeliDE Dil ve Edebiyat Araştırmaları Dergisi :Ö12 ► pp. 739 ff.
Peraldi, Sandrine
2016. De la traduction automatique brute à la post-édition professionnelle évoluée : le cas de la traduction financière. Revue française de linguistique appliquée Vol. XXI:1 ► pp. 67 ff.
Reyes Ayala, Brenda, Ryan Knudson, Jiangping Chen, Gaohui Cao & Xinyue Wang
2018. Metadata records machine translation combining multi‐engine outputs with limited parallel data. Journal of the Association for Information Science and Technology 69:1 ► pp. 47 ff.
Rico, Celia & María del Mar Sánchez Ramos
2023. The Ethics of Machine Translation Post-editing in the Translation Ecosystem. In Towards Responsible Machine Translation [Machine Translation: Technologies and Applications, 4], ► pp. 95 ff.
Santy, Sebastin, Kalika Bali, Monojit Choudhury, Sandipan Dandapat, Tanuja Ganu, Anurag Shukla, Jahanvi Shah & Vivek Seshadri
2021. ACM SIGCAS Conference on Computing and Sustainable Societies (COMPASS), ► pp. 156 ff.
Stahl, Jaroslav, Daša Munková, Ľubomír Benko & Elena Hudecová
2023. Maschinelle, posteditierte und menschliche Übersetzung publizistischer und populärwissenschaftlicher Texte aus dem Slowakischen ins Deutsche. Lebende Sprachen 68:2 ► pp. 259 ff.
Sun, Sanjun
2019. Measuring Difficulty in Translation and Post-editing: A Review. In Researching Cognitive Processes of Translation [New Frontiers in Translation Studies, ], ► pp. 139 ff.
Teixeira, Carlos S. C.
2013. Multilingual Systems, Translation Technology and Their Impact on the Translator’s Profession. In Where Humans Meet Machines, ► pp. 299 ff.
van Egdom, Gys-Walt & Mark Pluymaekers
2019. Quality According to Language Service Providers. In New Empirical Perspectives on Translation and Interpreting, ► pp. 139 ff.
Vaupot, Sonia
2021. Analyse des erreurs de traduction automatique pour la combinaison de langues slovène-français et perspectives pour une formation en post-édition. Matices en Lenguas Extranjeras 14:2 ► pp. 83 ff.
Venkatesan, Hari
2022. The fourth dimension in translation: time and disposability. Perspectives 30:4 ► pp. 662 ff.
Venkatesan, Hari
2023. Technology preparedness and translator training. Babel. Revue internationale de la traduction / International Journal of Translation / Revista Internacional de Traducción 69:5 ► pp. 666 ff.
Yamada, Masaru
2015. Can college students be post-editors? An investigation into employing language learners in machine translation plus post-editing settings. Machine Translation 29:1 ► pp. 49 ff.
Yang, Yanxia & Xiangling Wang
2023. Predicting student translators’ performance in machine translation post-editing: interplay of self-regulation, critical thinking, and motivation. Interactive Learning Environments 31:1 ► pp. 340 ff.
Yang, Zhengang, Hema Rosheny Mustafa & Zheng Yan
2022. On Postediting of Machine Translation and Workflow for Undergraduate Translation Program in China. Human Behavior and Emerging Technologies 2022 ► pp. 1 ff.
Yogi, Kuldeep Kumar, Nishith Joshi & Chandra Kumar Jha
2015. Quality Estimation of MT-Engine Output Using Language Models for Post-editing and Their Comparative Study. In Information Systems Design and Intelligent Applications [Advances in Intelligent Systems and Computing, 340], ► pp. 507 ff.
Zhao, Shengfang
2021. Post-editing Neural Machine Translation Versus Human Translation for Chinese Essays: A Pilot Study. In Diverse Voices in Chinese Translation and Interpreting [New Frontiers in Translation Studies, ], ► pp. 399 ff.
ÇETİNER, Caner
2021. Sustainability of translation as a profession: Changing roles of translators in light of the developments in machine translation systems. RumeliDE Dil ve Edebiyat Araştırmaları Dergisi :Ö9 ► pp. 575 ff.
[no author supplied]
[no author supplied]
2019. References. In Machine Translation and Global Research: Towards Improved Machine Translation Literacy in the Scholarly Community, ► pp. 97 ff.
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