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Publications

In press

The vocabulary demands of English and French L2 textbooks: A cross-lingual corpus study

Van Parys, A, De Wilde, V., Macken, L., & Montero Perez, M. (2023).

2023

Translations and Open Science - Exploring how translation technologies can support multilingualism in scholarly communication (.pdf)

Fiorini, S., Tezcan, A., Vanallemeersch, T., Szoc, S., Migdisi, K., Meeus, L., & Macken, L. (2023).

Adapting machine translation education to the neural era : a case study of MT quality assessment (.pdf)

Macken, L., Vanroy, B., & Tezcan, A. (2023).

Developing user-centred approaches to technological innovation in literary translation (DUAL-T) (.pdf)

Ruffo, P., Daems, J, & Macken, L. (2023).

The vocabulary demands of English and French L2 textbooks: A cross-lingual corpus study (.pdf)

Van Parys, A, De Wilde, V., Macken, L., & Montero Perez, M. (2023).

MATEO : MAchine Translation Evaluation Online (.pdf)

Vanroy, B., Tezcan, A., & Macken, L. (2023).

2022

GECO-MT : the Ghent Eye-tracking Corpus of Machine Translation (.pdf)

Colman, T., Fonteyne, M., Daems, J, Dirix, N., & Macken, L. (2022).

Writing in a second Language with Machine translation (WiLMa) (.pdf)

Fonteyne, M., Montero Perez, M., Daems, J, & Macken, L. (2022).

Google Translate in Foreign Language Education: Raising Teachers’ and Learners’ Awareness About Machine Translation (.pdf)

Fonteyne, M., Montero Perez, M., Daems, J, & Macken, L. (2022).

Writing in a Second Language with Machine Translation (.pdf)

Fonteyne, M., Montero Perez, M., Daems, J, & Macken, L. (2022).

Machine Translation enhanced literary translation (.pdf)

Macken, L., Daems, J, Vanroy, B., & Tezcan, A. (2022).

Literary translation as a three-stage process : machine translation, post-editing and revision (.pdf)

Macken, L., Vanroy, B., Desmet, L., & Tezcan, A. (2022).

The use of machine translation in real-life professional translation scenarios (.pdf)

Macken, L., Tezcan, A., Daems, J, & Vanroy, B. (2022).

The lexical demands of English and French L2 textbooks: A cross-lingual corpus study (.pdf)

Van Parys, A, De Wilde, V., Macken, L., & Montero Perez, M. (2022).

Measuring cross-lingual syntactic similarity (.pdf)

Vanroy, B., De Clercq, O., Tezcan, A., & Macken, L. (2022).

LeConTra : a learner corpus of English-to-Dutch news translation (.pdf)

Vanroy, B., & Macken, L. (2022).

2021

It's all in the eyes: using eye-tracking to assess the readability of machine translated literature

Colman, T., Fonteyne, M., Daems, J, & Macken, L. (2021).

It’s all in the eyes: an eye tracking experiment to assess the readability of machine translated literature

Colman, T., Fonteyne, M., Daems, J, & Macken, L. (2021).

Preface (.pdf)

De Clercq, O., Rigouts Terryn, A., Doğruöz, A.S., Tezcan, A., Vanroy, B., Labat, S., & Macken, L. (2021).

Building a new-generation corpus for empirical translation studies : the Dutch Parallel Corpus 2.0 (.pdf)

Reynaert, R., Macken, L., Tezcan, A., & De Sutter, G. (2021).

Metrics of syntactic equivalence to assess translation difficulty (.pdf)

Vanroy, B., De Clercq, O., Tezcan, A., Daems, J, & Macken, L. (2021).

Comparing the effect of product-based metrics on the translation process (.pdf)

Vanroy, B., Schaeffer, M., & Macken, L. (2021).

2020

Post-editing human translations and revising machine translations : impact on efficiency and quality (.pdf)

Daems, J, & Macken, L. (2020).

Literary machine translation under the magnifying glass : assessing the quality of an NMT-translated detective novel on document level (.pdf)

Fonteyne, M., Tezcan, A., & Macken, L. (2020).

Literary MT under the magnifying glass: Assessing the quality of an NMT-translated Agatha Christie novel (.pdf)

Fonteyne, M., Tezcan, A., & Macken, L. (2020).

Assessing the Comprehensibility of Automatic Translations (ArisToCAT) (.pdf)

Macken, L., Fonteyne, M., Tezcan, A., & Daems, J (2020).

Quantifying the effect of machine translation in a high-quality human translation production process (.pdf)

Macken, L., Prou, D., & Tezcan, A. (2020).

Estimating word-level quality of statistical machine translation output using monolingual information alone (.pdf)

Tezcan, A., Hoste, V., & Macken, L. (2020).

Gutenberg goes neural : comparing features of Dutch human translations with raw neural machine translation outputs in a corpus of English literary classics (.pdf)

Webster, R., Fonteyne, M., Tezcan, A., Macken, L., & Daems, J (2020).

2019

Interactive adaptive SMT versus interactive adaptive NMT : a user experience evaluation (.pdf)

Daems, J, & Macken, L. (2019).

Van CAT tot TenT : van computerondersteund vertalen tot vertaalomgevingen

Daems, J, & Macken, L. (2019).

Mysterie van de dag : waarom vindt een automatisch vertaalsysteem soms nieuwe woorden uit? (.pdf)

Macken, L. (2019).

NMT’s wonderland where people turn into rabbits : a study on the comprehensibility of newly invented words in NMT output (.pdf)

Macken, L., Van Brussel, LVB, & Daems, J (2019).

Pilot study on medical translations in lay language : post-editing by language specialists, domain specialists or both? (.pdf)

Rigouts Terryn, A., Macken, L., Lefever, E., Vander Stichele, R., Vanneste, K, & Buysschaert, J. (2019).

When a `sport' is a person and other issues for NMT of novels (.pdf)

Tezcan, A., Daems, J, & Macken, L. (2019).

Estimating post-editing time using a gold-standard set of machine translation errors (.pdf)

Tezcan, A., Hoste, V., & Macken, L. (2019).

Improving the translation environment for professional translators (.pdf)

Vandeghinste, V., Vanallemeersch, T., Augustinus, L., Bulté, B., Van Eynde, F., Pelemans, J., Verwimp, L., Wambacq, P., Heyman, G., Moens, M., van der Lek-Ciudin, I., Steurs, F., Rigouts Terryn, A., Lefever, E., Tezcan, A., Macken, L., Hoste, V., Daems, J, Buysschaert, J., Coppers, S., Van den Bergh, J., & Luyten, K. (2019).

Modelling word translation entropy and syntactic equivalence with machine learning (.pdf)

Vanroy, B., De Clercq, O., & Macken, L. (2019).

Predicting syntactic equivalence between source and target sentences (.pdf)

Vanroy, B., Tezcan, A., & Macken, L. (2019).

Correlating process and product data to get an insight into translation difficulty (.pdf)

Vanroy, B., De Clercq, O., & Macken, L. (2019).

2018

How do students cope with machine translation output of Multi-Word Units? An exploratory study (.pdf)

Daems, J, Carl, M., Vandepitte, S., Hartsuiker, R., & Macken, L. (2018).

Dutch compound splitting for bilingual terminology extraction (.pdf)

Macken, L., & Tezcan, A. (2018).

Measuring comprehension and perception of neural machine translated texts : a pilot study (.pdf)

Macken, L., & Ghyselen, I. (2018).

A fine-grained error analysis of NMT, PBMT and RBMT output for English-to-Dutch (.pdf)

Van Brussel, LVB, Tezcan, A., & Macken, L. (2018).

Smart Computer-Aided Translation Environment (SCATE): Highlights (.pdf)

Vandeghinste, V., Vanallemeersch, T., Bulté, B., Augustinus, L., Van Eynde, F., Pelemans, J., Verwimp, L., Wambacq, P., Heyman, G., Moens, M., van der Lek-Ciudin, I., Steurs, F., Rigouts Terryn, A., Lefever, E., Tezcan, A., Macken, L., Coppers, S., Brulmans, J., Van den Bergh, J., Luyten, K., & Coninx, K. (2018).