Arda Tezcan
Arda Tezcan
Senior Researcher, LT3, Ghent University
Verified email at
Cited by
Cited by
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
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
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
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
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
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
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
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
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
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
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
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
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
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
Improving the translation environment for professional translators
V Vandeghinste, T Vanallemeersch, L Augustinus, B Bulté, F Van Eynde, ...
Informatics 6 (2), 24, 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
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
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
Predicting syntactic equivalence between source and target sentences
B Vanroy, A Tezcan, L Macken
Computational Linguistics in the Netherlands Journal 9, 101-116, 2019
Dutch compound splitting for bilingual terminology extraction
L Macken, A Tezcan
Multiword Units in Machine Translation and Translation Technology 341, 147-162, 2018
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