Chantal Amrhein
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Supervised OCR error detection and correction using statistical and neural machine translation methods
C Amrhein, S Clematide
Journal for Language Technology and Computational Linguistics (JLCL) 33 (1 …, 2018
Post-editing productivity with neural machine translation: an empirical assessment of speed and quality in the banking and finance domain
S Läubli, C Amrhein, P Düggelin, B Gonzalez, A Zwahlen, M Volk
arXiv preprint arXiv:1906.01685, 2019
Building a parallel corpus on the world’s oldest banking magazine
M Volk, C Amrhein, N Aepli, M Müller, P Ströbel
Proceedings of the 13th Conference on Natural Language Processing (KONVENS …, 2016
Identifying weaknesses in machine translation metrics through minimum bayes risk decoding: A case study for comet
C Amrhein, R Sennrich
arXiv preprint arXiv:2202.05148, 2022
How Suitable Are Subword Segmentation Strategies for Translating Non-Concatenative Morphology?
C Amrhein, R Sennrich
arXiv preprint arXiv:2109.01100, 2021
On romanization for model transfer between scripts in neural machine translation
C Amrhein, R Sennrich
arXiv preprint arXiv:2009.14824, 2020
C-3MA: Tartu-Riga-Zurich translation systems for WMT17
M Rikters, C Amrhein, M Del, M Fishel
Proceedings of the Second Conference on Machine Translation, 382-388, 2017
On biasing transformer attention towards monotonicity
A Rios, C Amrhein, N Aepli, R Sennrich
arXiv preprint arXiv:2104.03945, 2021
ACES: Translation Accuracy Challenge Sets for Evaluating Machine Translation Metrics
C Amrhein, N Moghe, L Guillou
arXiv preprint arXiv:2210.15615, 2022
Don't Discard Fixed-Window Audio Segmentation in Speech-to-Text Translation
C Amrhein, B Haddow
arXiv preprint arXiv:2210.13363, 2022
Learning What to Share in Multi-Task Learning
C Amrhein
Post-Correcting OCR Errors Using Neural Machine Translation
C Amrhein
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