no code implementations • MTSummit 2021 • Simon Rieß, Matthias Huck, Alex Fraser
Sentence weighting is a simple and powerful domain adaptation technique.
no code implementations • ACL 2020 • Marion Weller-Di Marco, Alex Fraser, er
This paper studies strategies to model word formation in NMT using rich linguistic information, namely a word segmentation approach that goes beyond splitting into substrings by considering fusional morphology.
no code implementations • LREC 2020 • Leah Michel, Viktor Hangya, Alex Fraser, er
We use a publicly available Hiligaynon corpus with only 300K words, and match it with a comparable corpus in English.
no code implementations • LREC 2020 • Silvia Severini, Viktor Hangya, Alex Fraser, er, Hinrich Sch{\"u}tze
We participate in both the open and closed tracks of the shared task and we show improved results of our method compared to simple vector similarity based approaches.
no code implementations • WS 2019 • Dario Stojanovski, Alex Fraser, er
We describe LMU Munich{'}s machine translation system for English→German translation which was used to participate in the WMT19 shared task on supervised news translation.
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.
1 code implementation • ACL 2019 • Viktor Hangya, Alex Fraser, er
Mining parallel sentences from comparable corpora is important.
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 • 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 • 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 • Viktor Hangya, Alex Fraser, er
In this paper we describe LMU Munich{'}s submission for the \textit{WMT 2018 Parallel Corpus Filtering} shared task which addresses the problem of cleaning noisy parallel corpora.
no code implementations • WS 2018 • Dario Stojanovski, Alex Fraser, er
We show that NMT models taking advantage of context oracle signals can achieve considerable gains in BLEU, of up to 7. 02 BLEU for coreference and 1. 89 BLEU for coherence on subtitles translation.
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.
1 code implementation • ACL 2018 • Viktor Hangya, Fabienne Braune, Alex Fraser, er, Hinrich Sch{\"u}tze
Bilingual tasks, such as bilingual lexicon induction and cross-lingual classification, are crucial for overcoming data sparsity in the target language.
1 code implementation • NAACL 2018 • Fabienne Braune, Viktor Hangya, Tobias Eder, Alex Fraser, er
Bilingual word embeddings are useful for bilingual lexicon induction, the task of mining translations of given words.
no code implementations • CL 2017 • Hassan Sajjad, Helmut Schmid, Alex Fraser, er, Hinrich Sch{\"u}tze
After training, the unlabeled data is disambiguated based on the posterior probabilities of the two sub-models.
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 • EACL 2017 • Marion Weller-Di Marco, Alex Fraser, er, Sabine Schulte im Walde
Many errors in phrase-based SMT can be attributed to problems on three linguistic levels: morphological complexity in the target language, structural differences and lexical choice.
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