Search Results for author: Roman Grundkiewicz

Found 28 papers, 5 papers with code

Findings of the IWSLT 2022 Evaluation Campaign

no code implementations IWSLT (ACL) 2022 Antonios Anastasopoulos, Loïc Barrault, Luisa Bentivogli, Marcely Zanon Boito, Ondřej Bojar, Roldano Cattoni, Anna Currey, Georgiana Dinu, Kevin Duh, Maha Elbayad, Clara Emmanuel, Yannick Estève, Marcello Federico, Christian Federmann, Souhir Gahbiche, Hongyu Gong, Roman Grundkiewicz, Barry Haddow, Benjamin Hsu, Dávid Javorský, Vĕra Kloudová, Surafel Lakew, Xutai Ma, Prashant Mathur, Paul McNamee, Kenton Murray, Maria Nǎdejde, Satoshi Nakamura, Matteo Negri, Jan Niehues, Xing Niu, John Ortega, Juan Pino, Elizabeth Salesky, Jiatong Shi, Matthias Sperber, Sebastian Stüker, Katsuhito Sudoh, Marco Turchi, Yogesh Virkar, Alexander Waibel, Changhan Wang, Shinji Watanabe

The evaluation campaign of the 19th International Conference on Spoken Language Translation featured eight shared tasks: (i) Simultaneous speech translation, (ii) Offline speech translation, (iii) Speech to speech translation, (iv) Low-resource speech translation, (v) Multilingual speech translation, (vi) Dialect speech translation, (vii) Formality control for speech translation, (viii) Isometric speech translation.

Speech-to-Speech Translation Translation

Findings of the WMT 2021 Shared Task on Efficient Translation

no code implementations WMT (EMNLP) 2021 Kenneth Heafield, Qianqian Zhu, Roman Grundkiewicz

The machine translation efficiency task challenges participants to make their systems faster and smaller with minimal impact on translation quality.

Machine Translation Translation

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

On User Interfaces for Large-Scale Document-Level Human Evaluation of Machine Translation Outputs

no code implementations EACL (HumEval) 2021 Roman Grundkiewicz, Marcin Junczys-Dowmunt, Christian Federmann, Tom Kocmi

Recent studies emphasize the need of document context in human evaluation of machine translations, but little research has been done on the impact of user interfaces on annotator productivity and the reliability of assessments.

Machine Translation Translation

A Crash Course in Automatic Grammatical Error Correction

no code implementations COLING 2020 Roman Grundkiewicz, Christopher Bryant, Mariano Felice

Grammatical Error Correction (GEC) is the task of automatically detecting and correcting all types of errors in written text.

14 Grammatical Error Correction

From Research to Production and Back: Ludicrously Fast Neural Machine Translation

no code implementations WS 2019 Young Jin Kim, Marcin Junczys-Dowmunt, Hany Hassan, Alham Fikri Aji, Kenneth Heafield, Roman Grundkiewicz, Nikolay Bogoychev

Taking our dominating submissions to the previous edition of the shared task as a starting point, we develop improved teacher-student training via multi-agent dual-learning and noisy backward-forward translation for Transformer-based student models.

Machine Translation Translation

Minimally-Augmented Grammatical Error Correction

no code implementations WS 2019 Roman Grundkiewicz, Marcin Junczys-Dowmunt

There has been an increased interest in low-resource approaches to automatic grammatical error correction.

Grammatical Error Correction

Neural Machine Translation Techniques for Named Entity Transliteration

1 code implementation WS 2018 Roman Grundkiewicz, Kenneth Heafield

Transliterating named entities from one language into another can be approached as neural machine translation (NMT) problem, for which we use deep attentional RNN encoder-decoder models.

Automatic Post-Editing Grammatical Error Correction +2

Approaching Neural Grammatical Error Correction as a Low-Resource Machine Translation Task

1 code implementation NAACL 2018 Marcin Junczys-Dowmunt, Roman Grundkiewicz, Shubha Guha, Kenneth Heafield

Previously, neural methods in grammatical error correction (GEC) did not reach state-of-the-art results compared to phrase-based statistical machine translation (SMT) baselines.

Domain Adaptation Grammatical Error Correction +3

Near Human-Level Performance in Grammatical Error Correction with Hybrid Machine Translation

no code implementations NAACL 2018 Roman Grundkiewicz, Marcin Junczys-Dowmunt

We combine two of the most popular approaches to automated Grammatical Error Correction (GEC): GEC based on Statistical Machine Translation (SMT) and GEC based on Neural Machine Translation (NMT).

Grammatical Error Correction Machine Translation +1

Marian: Fast Neural Machine Translation in C++

2 code implementations ACL 2018 Marcin Junczys-Dowmunt, Roman Grundkiewicz, Tomasz Dwojak, Hieu Hoang, Kenneth Heafield, Tom Neckermann, Frank Seide, Ulrich Germann, Alham Fikri Aji, Nikolay Bogoychev, André F. T. Martins, Alexandra Birch

We present Marian, an efficient and self-contained Neural Machine Translation framework with an integrated automatic differentiation engine based on dynamic computation graphs.

Machine Translation Translation

Pushing the Limits of Translation Quality Estimation

no code implementations TACL 2017 Andr{\'e} F. T. Martins, Marcin Junczys-Dowmunt, Fabio N. Kepler, Ram{\'o}n Astudillo, Chris Hokamp, Roman Grundkiewicz

Translation quality estimation is a task of growing importance in NLP, due to its potential to reduce post-editing human effort in disruptive ways.

Automatic Post-Editing Translation

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