Neural fuzzy repair: Integrating fuzzy matches into neural machine translation B Bulté, A Tezcan 57th Annual Meeting of the Association-for-Computational-Linguistics (ACL …, 2019 | 63 | 2019 |
Quantifying the effect of machine translation in a high-quality human translation production process L Macken, D Prou, A Tezcan Informatics 7 (2), 12, 2020 | 40 | 2020 |
A fine-grained error analysis of NMT, PBMT and RBMT output for English-to-Dutch L Van Brussel, A Tezcan, L Macken Eleventh International Conference on Language Resources and Evaluation, 3799 …, 2018 | 39 | 2018 |
When a 'sport' is a person and other issues for NMT of novels A Tezcan, J Daems, L Macken Proceedings of the Qualities of Literary Machine Translation, 40-49, 2019 | 27 | 2019 |
SCATE Taxonomy and Corpus of Machine Translation Errors A Tezcan, V Hoste, L Macken Trends in e-tools and resources for translators and interpreters, 2016 | 22 | 2016 |
Literary machine translation under the magnifying glass: Assessing the quality of an NMT-translated detective novel on document level M Fonteyne, A Tezcan, L Macken 12th International Conference on Language Resources and Evaluation (LREC …, 2020 | 21 | 2020 |
A neural network architecture for detecting grammatical errors in statistical machine translation A Tezcan, V Hoste, L Macken The Prague Bulletin of Mathematical Linguistics 108 (1), 133-145, 2017 | 20 | 2017 |
Estimating word-level quality of statistical machine translation output using monolingual information alone A Tezcan, V Hoste, L Macken Natural Language Engineering 26 (1), 73-94, 2020 | 15 | 2020 |
Towards a better integration of fuzzy matches in neural machine translation through data augmentation A Tezcan, B Bulté, B Vanroy Informatics 8 (1), 7, 2021 | 14 | 2021 |
Gutenberg goes neural: Comparing features of dutch human translations with raw neural machine translation outputs in a corpus of english literary classics R Webster, M Fonteyne, A Tezcan, L Macken, J Daems Informatics 7 (3), 32, 2020 | 12 | 2020 |
UGENT-LT3 SCATE system for machine translation quality estimation A Tezcan, V Hoste, B Desmet, L Macken Proceedings of the Tenth Workshop on Statistical Machine Translation, 353-360, 2015 | 11 | 2015 |
Post-edited quality, post-editing behaviour and human evaluation: a case study I Depraetere, N De Sutter, A Tezcan Post-editing of Machine Translation, 78, 2014 | 11* | 2014 |
Detecting Grammatical Errors in Machine Translation Output Using Dependency Parsing and Treebank Querying A Tezcan, V Hoste, L Macken Baltic Journal of Modern Computing 4 (2), 203-217, 2016 | 10 | 2016 |
Metrics of syntactic equivalence to assess translation difficulty B Vanroy, OD Clercq, A Tezcan, J Daems, L Macken Explorations in empirical translation process research, 259-294, 2021 | 9 | 2021 |
Improving the translation environment for professional translators V Vandeghinste, T Vanallemeersch, L Augustinus, B Bulté, F Van Eynde, ... Informatics 6 (2), 24, 2019 | 9 | 2019 |
Smart Computer Aided Translation Environment V Vandeghinste, T Vanallemeersch, F Van Eynde, G Heyman, MF Moens, ... Annual conference of the European Association for Machine Translation-EAMT …, 2015 | 9 | 2015 |
SMT-CAT Integration in a Technical Domain. Handling XML mark-up using pre and post-editing processing methods A Tezcan, V Vandeghinste Proceedings of the 15th International Conference of the European Association …, 2011 | 8* | 2011 |
Estimating post-editing time using a gold-standard set of machine translation errors A Tezcan, V Hoste, L Macken Computer Speech & Language 55, 120-144, 2019 | 7 | 2019 |
Predicting syntactic equivalence between source and target sentences B Vanroy, A Tezcan, L Macken Computational Linguistics in the Netherlands Journal 9, 101-116, 2019 | 7 | 2019 |
Dutch compound splitting for bilingual terminology extraction L Macken, A Tezcan Multiword Units in Machine Translation and Translation Technology 341, 147-162, 2018 | 6 | 2018 |