4 citations · 7 across the 4 of their papers we have counts for
9 papers
Multilingual Unsupervised Neural Machine Translation with Denoising Adapters
Ahmet Üstün, Alexandre Bérard, Laurent Besacier +1
We consider the problem of multilingual unsupervised machine translation, translating to and from languages that only have monolingual data by using auxiliary parallel language pai…
Unsupervised Translation of German--Lower Sorbian: Exploring Training and Novel Transfer Methods on a Low-Resource Language
Lukas Edman, Ahmet Üstün, Antonio Toral +1
This paper describes the methods behind the systems submitted by the University of Groningen for the WMT 2021 Unsupervised Machine Translation task for German--Lower Sorbian (DE--D…
On the Difficulty of Translating Free-Order Case-Marking Languages
Arianna Bisazza, Ahmet Üstün, Stephan Sportel
Identifying factors that make certain languages harder to model than others is essential to reach language equality in future Natural Language Processing technologies. Free-order c…
From Masked Language Modeling to Translation: Non-English Auxiliary Tasks Improve Zero-shot Spoken Language Understanding
Rob van der Goot, Ibrahim Sharaf, Aizhan Imankulova +6
The lack of publicly available evaluation data for low-resource languages limits progress in Spoken Language Understanding (SLU). As key tasks like intent classification and slot f…
On the Effectiveness of Dataset Embeddings in Mono-lingual,Multi-lingual and Zero-shot Conditions
Rob van der Goot, Ahmet Üstün, Barbara Plank
Recent complementary strands of research have shown that leveraging information on the data source through encoding their properties into embeddings can lead to performance increas…
FiSSA at SemEval-2020 Task 9: Fine-tuned For Feelings
Bertelt Braaksma, Richard Scholtens, Stan van Suijlekom +2
In this paper, we present our approach for sentiment classification on Spanish-English code-mixed social media data in the SemEval-2020 Task 9. We investigate performance of variou…