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Institute of Formal and Applied Linguistics


Charles University, Czech Republic
Faculty of Mathematics and Physics

ÚFAL
Ivana Kvapilíková

Ivana Kvapilíková Ivana Muzikářová

Main Research Interests

  • Neural machine translation, unsupervised machine translation
  • Multilingual representation learning
  • Parallel corpus mining
  • Domain adaptation of machine translation

Projects

Babel Octopus: Robust Multi-Source Speech Translation (START/SCI/089)
The project proposes methods for creating a robust simultaneous multi-source speech-to-text translation.
1.4.2021 - 31.3.2023


Neural machine translation for low-resource languages (GAUK 1050119)
The aim of the project is to investigate methods of training machine translation models with limited access to manually translated texts. 
1.1.2019 - 31.12.2021

Neural Representations in Multi-modal and Multi-lingual Modelling (NEUREM3) (GAČR EXPRO 19-26934X)
The NEUREM3 project encompasses basic research in speech processing (SP) and natural language processing (NLP) with accent on multi-linguality and multi-modality(speech and text processing with the support of visual information).
1.1.2019 - 31.12.2024

Curriculum Vitae

2018 – present                PhD program in Computational Linguistics

Charles University in Prague, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics

Dissertation topic: Towards machine translation based on monolingual texts

 

2012 – 2015                     Master's degree in Economics & Finance (summa cum laude)

2009 – 2012                     Bachelor's degree in Economics (summa cum laude)

Charles University in Prague, Faculty of Social Sciences, Institute of Economic Studies

Master's thesis topic: Measuring systemic risk in time-frequency domain

 

2015                                  Study exchange at University of Otago, Dunedin, New Zealand

2013                                  Study exchange at Universdad de Granada, Granada, Spain

Selected Bibliography

Ivana Kvapilíková, Mikel Artetxe, Gorka Labaka, Eneko Agirre, Ondřej Bojar (2020): Unsupervised Multilingual Sentence Embeddings for Parallel Corpus Mining. In: Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics: Student Research Workshop, pp. 255-262, Association for Computational Linguistics, Stroudsburg, PA, USA, ISBN 978-1-952148-03-3 (url, local PDF, obd, bibtex)

Ivana Kvapilíková, Tom Kocmi, Ondřej Bojar (2020): CUNI Systems for the Unsupervised and Very Low Resource Translation Task in WMT20. In: Fifth Conference on Machine Translation - Proceedings of the Conference, pp. 1123-1128, Association for Computational Linguistics, Stroudsburg, PA, USA, ISBN 978-1-948087-81-0 (local PDF, obd, bibtex)

Ivana Kvapilíková, Dominik Macháček, Ondřej Bojar (2019): CUNI Systems for the Unsupervised News Translation Task in WMT 2019. In: Fourth Conference on Machine Translation - Proceedings of the Conference, pp. 241-248, Association for Computational Linguistics, Stroudsburg, PA, USA, ISBN 978-1-950737-27-7 (pdf, obd, bibtex)