Wietse de Vries
Hi! I am a postdoctoral researcher in the Computational Linguistics group of the University of Groningen (The Netherlands). My current work is on low-resource speech technology 🗣️.
Current hobbies include beekeeping 🐝, mycology 🍄, meadmaking 🍯, bouldering 🪨 and ice skating ⛸️.
Profiles
Academic bio
- 2024-nowPostdoctoral researcher in Speech Technology, University of Groningen.
- 2020-2024PhD in Computational Linguistics, University of Groningen PhD thesis: Evaluation and Adaptation of Neural Language Models for Under-Resourced Languages .
- 2018-2020Ma in Information Science, University of Groningen, cum laude.
- 2015-2018BSc in Information Science, University of Groningen, cum laude.
Publications
- Yun Hao, Reihaneh Amooie, Wietse de Vries, Thomas Tienkamp, Rik van Noord, Martijn Wieling (2024)
- Hedwig Sekeres, Wilbert Heeringa, Wietse de Vries, Oscar Yde Zwagers, Martijn Wieling, Goffe Jensma (2024)
- Clara Egger, Tommaso Caselli, Georgios Tziafas, Eugénie de Saint Phalle, Wietse de Vries (2024)
- Wietse de Vries, Martijn Wieling, Malvina Nissim (2023)
- Wietse de Vries, Martijn Wieling, Malvina Nissim (2022)
- Martijn Bartelds, Wietse de Vries, Faraz Sanal, Caitlin Richter, Mark Liberman, Martijn Wieling (2022)Neural Representations for Modeling Variation in Speech Journal of Phonetics 92
- Wietse de Vries*, Martijn Bartelds*, Malvina Nissim, Martijn Wieling *equal contribution (2021)Adapting Monolingual Models: Data can be Scarce when Language Similarity is High Findings of ACL 2021
- Wietse de Vries, Malvina Nissim (2021)
- Georgios Tziafas, Eugenie de Saint-Phalle, Wietse de Vries, Clara Egger, Tommaso Caselli (2021)A Multilingual Approach to Identify and Classify Exceptional Measures against COVID-19 Natural Legal Language Processing Workshop 2021
- Wietse de Vries, Andreas van Cranenburgh, Malvina Nissim (2020)
- Wietse de Vries, Andreas van Cranenburgh, Arianna Bisazza, Tommaso Caselli, Gertjan van Noord, Malvina Nissim (2019)
- Wietse de Vries (2019)Cognitively Plausible Computational Models of Lexical Processing Can Explain Variance in Human Word Predictions and Reading Times Artificial Intelligence and Machine Learning (BNAIC 2019)