| Getting gender right in neural machine translation E Vanmassenhove, C Hardmeier, A Way arXiv preprint arXiv:1909.05088, 2019 | 239 | 2019 |
| Lost in translation: Loss and decay of linguistic richness in machine translation E Vanmassenhove, D Shterionov, A Way arXiv preprint arXiv:1906.12068, 2019 | 128 | 2019 |
| Machine translationese: Effects of algorithmic bias on linguistic complexity in machine translation E Vanmassenhove, D Shterionov, M Gwilliam arXiv preprint arXiv:2102.00287, 2021 | 95 | 2021 |
| A Case Study of Natural Gender Phenomena in Translation-A Comparison of Google Translate, Bing Microsoft Translator and DeepL for English to Italian, French and Spanish AA Rescigno, E Vanmassenhove, J Monti, A Way CEUR Workshop Proceedings, 359-364, 2020 | 48 | 2020 |
| Neutral rewriter: A rule-based and neural approach to automatic rewriting into gender-neutral alternatives E Vanmassenhove, C Emmery, D Shterionov arXiv preprint arXiv:2109.06105, 2021 | 47 | 2021 |
| Translation resources and translator disempowerment J Moorkens, D Lewis, W Reijers, E Vanmassenhove, A Way European Language Resource Association, 2016 | 24 | 2016 |
| Investigating'Aspect'in NMT and SMT: translating the English simple past and present perfect E Vanmassenhove, J Du, A Way Computational Linguistics in the Netherlands Journal (CLIN) 7, 109-128, 2017 | 22 | 2017 |
| Generating gender augmented data for NLP N Jain, M Popovic, D Groves, E Vanmassenhove arXiv preprint arXiv:2107.05987, 2021 | 15 | 2021 |
| Prediction of Emotions from Text using Sentiment Analysis for Expressive Speech Synthesis. E Vanmassenhove, JP Cabral, F Haider SSW, 21-26, 2016 | 15 | 2016 |
| Europarl datasets with demographic speaker information E Vanmassenhove, C Hardmeier European Association for Machine Translation, 2018 | 14 | 2018 |
| gENder-IT: An Annotated English-Italian Parallel Challenge Set for Cross-Linguistic Natural Gender Phenomena E Vanmassenhove, J Monti Proceeding of the 3rd Workshop on Gender Bias in Natural Language Processing …, 2021 | 11 | 2021 |
| SuperNMT: Neural machine translation with semantic supersenses and syntactic supertags E Vanmassenhove, A Way Association for Computational Linguistics (ACL), 2018 | 11 | 2018 |
| The Ecological Footprint of Neural Machine Translation Systems D Shterionov, E Vanmassenhove Towards Responsible Machine Translation: Ethical and Legal Considerations in …, 2022 | 10 | 2022 |
| Improving subject-verb agreement in SMT E Vanmassenhove, J Du, A Way | 7 | 2016 |
| On the integration of linguistic features into statistical and neural machine translation E Vanmassenhove Dublin City University, 2019 | 6 | 2019 |
| 9 Gender Bias in Machine Translation and the Era of Large Language Models E Vanmassenhove Gendered Technology in Translation and Interpreting: Centering Rights in the …, 2024 | 4 | 2024 |
| Minds: Big questions for linguistics in the age of AI A Backus, M Cohen, N Cohn, M Faber, E Krahmer, S Laparle, E Maier, ... Linguistics in the Netherlands 40 (1), 301-308, 2023 | 4 | 2023 |
| ABI Neural Ensemble Model for Gender Prediction: Adapt Bar-Ilan Submission for the CLIN29 Shared Task on Gender Prediction E Vanmassenhove, A Moryossef, A Poncelas, A Way, D Shterionov Computational Linguistics in the Netherlands (CLIN) 29, 2019 | 4* | 2019 |
| The ADAPT entry to the Blizzard Challenge 2016 JP Cabral, C Saam, E Vanmassenhove, S Bradley, F Haider Proceedings of the Blizzard Challenge 2016, 2016 | 4 | 2016 |
| On the need for a global declaration of ethical principles for experimentation with personal data W Reijers, E Vanmassenhove, D Lewis, J Moorkens ETHI-CA2 2016: ETHics In Corpus Collection, Annotation & Application …, 2016 | 4 | 2016 |
Andy WayADAPT Centre, Dublin City UniversityVerified email at adaptcentre.ie
