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ELITR Non-Native Speech Translation at IWSLT 2020

Machácek, Dominik; Sagar, Sangeet; Žilinec, Matúš; Bojar, Ondřej; Nguyen, Thai-Son; Schneider, Felix; Williams, Philip; Yao, Yuekun; Kratochvíl, Jonáš

Abstract:

This paper is an ELITR system submission for the non-native speech translation task at IWSLT 2020. We describe systems for offline ASR, real-time ASR, and our cascaded approach to offline SLT and real-time SLT. We select our primary candidates from a pool of pre-existing systems, develop a new end-toend general ASR system, and a hybrid ASR trained on non-native speech. The provided small validation set prevents us from carrying out a complex validation, but we submit all the unselected candidates for contrastive evaluation on the test set.


Verlagsausgabe §
DOI: 10.5445/IR/1000166166
Veröffentlicht am 11.01.2024
Originalveröffentlichung
DOI: 10.18653/v1/2020.iwslt-1.25
Dimensions
Zitationen: 1
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Anthropomatik und Robotik (IAR)
Publikationstyp Proceedingsbeitrag
Publikationsjahr 2020
Sprache Englisch
Identifikator ISBN: 978-1-952148-07-1
KITopen-ID: 1000166166
Erschienen in Proceedings of the 17th International Conference on Spoken Language Translation. Ed.: M. Federico, A. Waibel, K. Knight, S. Nakamura, H. Ney, J. Niehues, S. Stüker, D. Wu, J. Mariani, F. Yvon
Veranstaltung 17. International Conference on Spoken Language Translation (IWSLT 2020), Online, 09.07.2020 – 10.07.2020
Verlag Association for Computational Linguistics (ACL)
Seiten 200-208
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