Search Results for author: Matthias Huck

Found 41 papers, 0 papers with code

Findings of the 2021 Conference on Machine Translation (WMT21)

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.

Machine Translation Translation

Contextual Refinement of Translations: Large Language Models for Sentence and Document-Level Post-Editing

no code implementations23 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.

Machine Translation NMT +2

Enhancing Supervised Learning with Contrastive Markings in Neural Machine Translation Training

no code implementations17 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.

Machine Translation NMT +1

Modeling Target-Side Morphology in Neural Machine Translation: A Comparison of Strategies

no code implementations25 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.

LEMMA Machine Translation +3

The LMU Munich Unsupervised Machine Translation System for WMT19

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.

Denoising Language Modelling +3

Better OOV Translation with Bilingual Terminology Mining

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.

Machine Translation NMT +2

Cross-lingual Annotation Projection Is Effective for Neural Part-of-Speech Tagging

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.

Part-Of-Speech Tagging POS +1

LMU Munich's Neural Machine Translation Systems at WMT 2018

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.

Domain Adaptation Translation +1

Enhancing Access to Online Education: Quality Machine Translation of MOOC Content

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.

Machine Translation Sentiment Analysis +1

Cannot find the paper you are looking for? You can Submit a new open access paper.