no code implementations • EAMT 2020 • Lukas Fischer, Samuel Läubli
Machine translation (MT) has been shown to produce a number of errors that require human post-editing, but the extent to which professional human translation (HT) contains such errors has not yet been compared to MT.
1 code implementation • 18 May 2023 • Chantal Amrhein, Florian Schottmann, Rico Sennrich, Samuel Läubli
We hypothesise that creating training data in the reverse direction, i. e. starting from gender-fair text, is easier for morphologically complex languages and show that it matches the performance of state-of-the-art rewriting models for English.
no code implementations • 11 Nov 2020 • Samuel Läubli, Patrick Simianer, Joern Wuebker, Geza Kovacs, Rico Sennrich, Spence Green
Widely used computer-aided translation (CAT) tools divide documents into segments such as sentences and arrange them in a side-by-side, spreadsheet-like view.
no code implementations • 8 Jun 2020 • Lukas Fischer, Samuel Läubli
Machine translation (MT) has been shown to produce a number of errors that require human post-editing, but the extent to which professional human translation (HT) contains such errors has not yet been compared to MT.
1 code implementation • 3 Apr 2020 • Samuel Läubli, Sheila Castilho, Graham Neubig, Rico Sennrich, Qinlan Shen, Antonio Toral
The quality of machine translation has increased remarkably over the past years, to the degree that it was found to be indistinguishable from professional human translation in a number of empirical investigations.
no code implementations • WS 2019 • Samuel Läubli, Chantal Amrhein, Patrick Düggelin, Beatriz Gonzalez, Alena Zwahlen, Martin Volk
Neural machine translation (NMT) has set new quality standards in automatic translation, yet its effect on post-editing productivity is still pending thorough investigation.
1 code implementation • EMNLP 2018 • Samuel Läubli, Rico Sennrich, Martin Volk
Recent research suggests that neural machine translation achieves parity with professional human translation on the WMT Chinese--English news translation task.
4 code implementations • EACL 2017 • Rico Sennrich, Orhan Firat, Kyunghyun Cho, Alexandra Birch, Barry Haddow, Julian Hitschler, Marcin Junczys-Dowmunt, Samuel Läubli, Antonio Valerio Miceli Barone, Jozef Mokry, Maria Nădejde
We present Nematus, a toolkit for Neural Machine Translation.
no code implementations • 19 May 2016 • Alena Zwahlen, Olivier Carnal, Samuel Läubli
We describe a machine learning based method to identify incorrect entries in translation memories.