no code implementations • WS 2015 • Ond{\v{r}}ej Bojar, Rajen Chatterjee, Christian Federmann, Barry Haddow, Matthias Huck, Chris Hokamp, Philipp Koehn, Varvara Logacheva, Christof Monz, Matteo Negri, Matt Post, Carolina Scarton, Lucia Specia, Marco Turchi
no code implementations • LREC 2016 • Valia Kordoni, Antal Van den Bosch, Katia Lida Kermanidis, Vilelmini Sosoni, Kostadin Cholakov, Iris Hendrickx, Matthias Huck, Andy Way
The present work is an overview of the TraMOOC (Translation for Massive Open Online Courses) research and innovation project, a machine translation approach for online educational content.
no code implementations • WS 2016 • Jan-Thorsten Peter, Tamer Alkhouli, Hermann Ney, Matthias Huck, Fabienne Braune, Alex Fraser, er, Ale{\v{s}} Tamchyna, Ond{\v{r}}ej Bojar, Barry Haddow, Rico Sennrich, Fr{\'e}d{\'e}ric Blain, Lucia Specia, Jan Niehues, Alex Waibel, Alex Allauzen, re, Lauriane Aufrant, Franck Burlot, Elena Knyazeva, Thomas Lavergne, Fran{\c{c}}ois Yvon, M{\=a}rcis Pinnis, Stella Frank
Ranked #12 on Machine Translation on WMT2016 English-Romanian
no code implementations • WS 2016 • Ond{\v{r}}ej Bojar, Rajen Chatterjee, Christian Federmann, Yvette Graham, Barry Haddow, Matthias Huck, Antonio Jimeno Yepes, Philipp Koehn, Varvara Logacheva, Christof Monz, Matteo Negri, Aur{\'e}lie N{\'e}v{\'e}ol, Mariana Neves, Martin Popel, Matt Post, Raphael Rubino, Carolina Scarton, Lucia Specia, Marco Turchi, Karin Verspoor, Marcos Zampieri
no code implementations • WS 2016 • Ond{\v{r}}ej Bojar, Christian Buck, Rajen Chatterjee, Christian Federmann, Liane Guillou, Barry Haddow, Matthias Huck, Antonio Jimeno Yepes, Aur{\'e}lie N{\'e}v{\'e}ol, Mariana Neves, Pavel Pecina, Martin Popel, Philipp Koehn, Christof Monz, Matteo Negri, Matt Post, Lucia Specia, Karin Verspoor, J{\"o}rg Tiedemann, Marco Turchi
no code implementations • EACL 2017 • Matthias Huck, Ale{\v{s}} Tamchyna, Ond{\v{r}}ej Bojar, Alex Fraser, er
Translating into morphologically rich languages is difficult.
no code implementations • WS 2017 • Ond{\v{r}}ej Bojar, Rajen Chatterjee, Christian Federmann, Yvette Graham, Barry Haddow, Shu-Jian Huang, Matthias Huck, Philipp Koehn, Qun Liu, Varvara Logacheva, Christof Monz, Matteo Negri, Matt Post, Raphael Rubino, Lucia Specia, Marco Turchi
no code implementations • WS 2018 • Matthias Huck, Dario Stojanovski, Viktor Hangya, Alex Fraser, er
The systems were used for our participation in the WMT18 biomedical translation task and in the shared task on machine translation of news.
no code implementations • WS 2018 • Dario Stojanovski, Viktor Hangya, Matthias Huck, Alex Fraser, er
We describe LMU Munich{'}s unsupervised machine translation systems for English↔German translation.
no code implementations • EMNLP 2018 • Ond{\v{r}}ej Bojar, Rajen Chatterjee, Christian Federmann, Mark Fishel, Yvette Graham, Barry Haddow, Matthias Huck, Antonio Jimeno Yepes, Philipp Koehn, Christof Monz, Matteo Negri, Aur{\'e}lie N{\'e}v{\'e}ol, Mariana Neves, Matt Post, Lucia Specia, Marco Turchi, Karin Verspoor
no code implementations • WS 2019 • Matthias Huck, Diana Dutka, Alex Fraser, er
We tackle the important task of part-of-speech tagging using a neural model in the zero-resource scenario, where we have no access to gold-standard POS training data.
no code implementations • ACL 2019 • Matthias Huck, Viktor Hangya, Alex Fraser, er
In our experiments we use a system trained on Europarl and mine sentences containing medical terms from monolingual data.
no code implementations • WS 2019 • Lo{\"\i}c Barrault, Ond{\v{r}}ej Bojar, Marta R. Costa-juss{\`a}, Christian Federmann, Mark Fishel, Yvette Graham, Barry Haddow, Matthias Huck, Philipp Koehn, Shervin Malmasi, Christof Monz, Mathias M{\"u}ller, Santanu Pal, Matt Post, Marcos Zampieri
This paper presents the results of the premier shared task organized alongside the Conference on Machine Translation (WMT) 2019.
no code implementations • WS 2019 • Dario Stojanovski, Viktor Hangya, Matthias Huck, Alex Fraser, er
We describe LMU Munich{'}s machine translation system for German→Czech translation which was used to participate in the WMT19 shared task on unsupervised news translation.
no code implementations • EMNLP 2020 • Loïc Barrault, Magdalena Biesialska, Ondřej Bojar, Marta R. Costa-jussà, Christian Federmann, Yvette Graham, Roman Grundkiewicz, Barry Haddow, Matthias Huck, Eric Joanis, Tom Kocmi, Philipp Koehn, Chi-kiu Lo, Nikola Ljubešić, Christof Monz, Makoto Morishita, Masaaki Nagata, Toshiaki Nakazawa, Santanu Pal, Matt Post, Marcos Zampieri
In the news task, participants were asked to build machine translation systems for any of 11 language pairs, to be evaluated on test sets consisting mainly of news stories.
no code implementations • 25 Mar 2022 • Marion Weller-Di Marco, Matthias Huck, Alexander Fraser
Key challenges of rich target-side morphology in data-driven machine translation include: (1) A large amount of differently inflected word surface forms entails a larger vocabulary and thus data sparsity.
no code implementations • 17 Jul 2023 • Nathaniel Berger, Miriam Exel, Matthias Huck, Stefan Riezler
Supervised learning in Neural Machine Translation (NMT) typically follows a teacher forcing paradigm where reference tokens constitute the conditioning context in the model's prediction, instead of its own previous predictions.
no code implementations • 23 Oct 2023 • Sai Koneru, Miriam Exel, Matthias Huck, Jan Niehues
Building on the LLM's exceptional ability to process and generate lengthy sequences, we also propose extending our approach to document-level translation.
no code implementations • MTSummit 2021 • Simon Rieß, Matthias Huck, Alex Fraser
Sentence weighting is a simple and powerful domain adaptation technique.
no code implementations • WMT (EMNLP) 2021 • Farhad Akhbardeh, Arkady Arkhangorodsky, Magdalena Biesialska, Ondřej Bojar, Rajen Chatterjee, Vishrav Chaudhary, Marta R. Costa-Jussa, Cristina España-Bonet, Angela Fan, Christian Federmann, Markus Freitag, Yvette Graham, Roman Grundkiewicz, Barry Haddow, Leonie Harter, Kenneth Heafield, Christopher Homan, Matthias Huck, Kwabena Amponsah-Kaakyire, Jungo Kasai, Daniel Khashabi, Kevin Knight, Tom Kocmi, Philipp Koehn, Nicholas Lourie, Christof Monz, Makoto Morishita, Masaaki Nagata, Ajay Nagesh, Toshiaki Nakazawa, Matteo Negri, Santanu Pal, Allahsera Auguste Tapo, Marco Turchi, Valentin Vydrin, Marcos Zampieri
This paper presents the results of the newstranslation task, the multilingual low-resourcetranslation for Indo-European languages, thetriangular translation task, and the automaticpost-editing task organised as part of the Con-ference on Machine Translation (WMT) 2021. In the news task, participants were asked tobuild machine translation systems for any of10 language pairs, to be evaluated on test setsconsisting mainly of news stories.
no code implementations • EAMT 2022 • Bianka Buschbeck, Jennifer Mell, Miriam Exel, Matthias Huck
This paper addresses the automatic translation of conversational content in a business context, for example support chat dialogues.