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Publications

In press

Automatic detection of (potential) factors in the source text leading to gender bias in machine translation (.pdf)

Hackenbuchner, J., Daems, J, & Tezcan, A. (2024).

Systematic, Stereotypical or an Educated Guess? Gender inference by humans and machine translation systems of words in and out of context (.pdf)

Hackenbuchner, J., Daems, J, & Tezcan, A. (2024).

Can We Interpret Gender? Using Contrastive Explanations to Understand Gender Choices by Translation Systems (.pdf)

Hackenbuchner, J., Daems, J, & Tezcan, A. (2025).

2025

Adding word sense awareness to computer-assisted language learning methods : a tailor-made word sense disambiguation method for Spanish as a foreign language (.pdf)

Degraeuwe, JRD, Goethals, P., & Tezcan, A. (2025).

Gender bias and the role of context in human perception and machine translation (.pdf)

Hackenbuchner, J., Daems, J, & Tezcan, A. (2025).

Gender Bias and the Role of Context in Human Perception and Machine Translation (.pdf)

Hackenbuchner, J., Daems, J, & Tezcan, A. (2025).

Machine translation to inform asylum seekers : intermediate findings from the MaTIAS project (.pdf)

Macken, L., van Hest, E, Tezcan, A., Lumingu, M., Maryns, K, & De Wilde, J. (2025).

Tailoring machine translation for scientific literature through topic filtering and fuzzy match augmentation (.pdf)

Moerman, T.M., Vanallemeersch, T., Szoc, S., & Tezcan, A. (2025).

2024

Intelligent Vocabulary and Example Selection for Spanish vocabulary learning (IVESS): project data

Degraeuwe, JRD, Goethals, P., Macken, L., & Tezcan, A. (2024).

You shall know a word’s gender by the company it keeps : comparing the role of context in human gender assumptions with MT (.pdf)

Hackenbuchner, J., Tezcan, A., Maladry, A, & Daems, J (2024).

You Shall Know a Word’s Gender by the Company it Keeps: Comparing the Role of Context in Human Gender Assumptions with MT (.pdf)

Hackenbuchner, J., Maladry, A, Daems, J, & Tezcan, A. (2024).

Automatic detection of (potential) factors in the source text leading to gender bias in machine translation (.pdf)

Hackenbuchner, J., Daems, J, & Tezcan, A. (2024).

Automatische tekstgeneratie (.pdf)

Lefever, E., & Tezcan, A. (2024).

MaTIAS : Machine Translation to Inform Asylum Seekers (.pdf)

Macken, L., van Hest, E, Tezcan, A., Lumingu, M., Maryns, K, & De Wilde, J. (2024).

Machine translation for open scholarly communication : examining the relationship between translation quality and reading effort (.pdf)

Macken, L., De Wilde, V., & Tezcan, A. (2024).

Automatische vertaling (.pdf)

Macken, L., & Tezcan, A. (2024).

Leveraging synthetic monolingual data for fuzzy-match augmentation in neural machine translation : a preliminary study (.pdf)

Moerman, T.M., & Tezcan, A. (2024).

Improving fuzzy match augmented neural machine translation in specialised domains through synthetic data (.pdf)

Tezcan, A., Skidanova, A., & Moerman, T.M. (2024).

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).

MATEO : MAchine Translation Evaluation Online (.pdf)

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

2022

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

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

Machine Translation enhanced literary translation (.pdf)

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

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

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

Evaluating the impact of integrating similar translations into neural machine translation (.pdf)

Tezcan, A., & Bulté, B. (2022).

Dynamic adaptation of neural machine-translation systems through translation exemplars (.pdf)

Tezcan, A. (2022).

Integrating fuzzy matches into sentence-level quality estimation for neural machine translation (.pdf)

Tezcan, A. (2022).

Measuring cross-lingual syntactic similarity (.pdf)

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

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).

Towards a better integration of fuzzy matches in neural machine translation through data augmentation (.pdf)

Tezcan, A., Bulté, B., & Vanroy, B. (2021).

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

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

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).

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

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

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

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

Neural fuzzy repair : integrating fuzzy matches into neural machine translation (.pdf)

Bulté, B., & Tezcan, A. (2019).

Vocabulary selection for didactic purposes : report on a machine learning approach (.pdf)

Goethals, P., Tezcan, A., & Degraeuwe, JRD (2019).

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

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

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

Tezcan, A., Daems, J, & 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).

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

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

2018

Dutch compound splitting for bilingual terminology extraction (.pdf)

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