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Samuel Läubli
Samuel Läubli
Textshuttle / Department of Computational Linguistics, University of Zurich
Dirección de correo verificada de cl.uzh.ch - Página principal
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Nematus: a toolkit for neural machine translation
R Sennrich, O Firat, K Cho, A Birch, B Haddow, J Hitschler, ...
Proceedings of the EACL 2017 Software Demonstrations, 65–68, 2017
4482017
Has Machine Translation Achieved Human Parity? A Case for Document-level Evaluation
S Läubli, R Sennrich, M Volk
Proceedings of EMNLP 2018, 4791–4796, 2018
3142018
A Set of Recommendations for Assessing Human–Machine Parity in Language Translation
S Läubli, S Castilho, G Neubig, R Sennrich, Q Shen, A Toral
Journal of Artificial Intelligence Research 67, 653–672, 2020
1202020
Assessing Post-Editing Efficiency in a Realistic Translation Environment
S Läubli, M Fishel, G Massey, M Ehrensberger-Dow, M Volk
Proceedings of MT Summit XIV Workshop on Post-editing Technology and …, 2013
1072013
When Google Translate is better than some human colleagues, those people are no longer colleagues
S Läubli, D Orrego-Carmona
Proceedings of Translating and the Computer 39, 59–69, 2017
772017
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
Proceedings of MT Summit, 267–272, 2019
452019
Translation technology research and human–computer interaction (HCI)
S Läubli, S Green
The Routledge Handbook of Translation and Technology, 2019
212019
Exploiting Biased Models to De-bias Text: A Gender-Fair Rewriting Model
C Amrhein, F Schottmann, R Sennrich, S Läubli
Proceedings of ACL 2023, 4486–4506, 2023
132023
Statistical modelling and automatic tagging of human translation processes
S Läubli, U Germann
New directions in empirical translation process research: Exploring the …, 2016
122016
The Impact of Text Presentation on Translator Performance
S Läubli, P Simianer, J Wuebker, G Kovacs, R Sennrich, S Green
Target: International Journal of Translation Studies 34 (2), 309–342, 2022
102022
What's the Difference Between Professional Human and Machine Translation? A Blind Multi-language Study on Domain-specific MT
L Fischer, S Läubli
Proceedings of EAMT 2020, 215–224, 2020
92020
Combining Statistical Machine Translation and Translation Memories with Domain Adaptation
S Läubli, M Fishel, M Volk, M Weibel
Proceedings of the 19th Nordic Conference of Computational Linguistics …, 2013
92013
Towards mapping of alpine route descriptions
M Piotrowski, S Läubli, M Volk
Proceedings of the 6th Workshop on Geographic Information Retrieval, 1-2, 2010
72010
Statistical Machine Translation for Automobile Marketing Texts
S Läubli, M Fishel, M Weibel, M Volk
Proceedings of MT Summit XIV, 2013
52013
Machine translation for professional translators
S Läubli
University of Zurich, 2020
32020
mtrain: A Convenience Tool for Machine Translation
S Läubli, M Müller, B Horat, M Volk
Proceedings of EAMT 2018, 357, 2018
32018
Automatic TM Cleaning through MT and POS Tagging: Autodesk's Submission to the NLP4TM 2016 Shared Task
A Zwahlen, O Carnal, S Läubli
arXiv preprint arXiv:1605.05906, 2016
32016
Sentiment Analysis for Media Reputation Research
S Läubli, M Schranz, U Christen, M Klenner
Proceedings of KONVENS 2012 (PATHOS 2012 workshop), 274-281, 2012
32012
MT developers
M Volk, S Läubli
Handbook of the Language Industry: Contexts, Resources and Profiles 20, 101, 2024
2024
Translation technology
S Läubli, S Green
The Routledge Handbook of Translation and Technology, 370, 2019
2019
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Artículos 1–20