@inproceedings{vazquez-etal-2020-university,
title = "The {U}niversity of {H}elsinki Submission to the {IWSLT}2020 Offline {S}peech{T}ranslation Task",
author = {V{\'a}zquez, Ra{\'u}l and
Aulamo, Mikko and
Sulubacak, Umut and
Tiedemann, J{\"o}rg},
editor = {Federico, Marcello and
Waibel, Alex and
Knight, Kevin and
Nakamura, Satoshi and
Ney, Hermann and
Niehues, Jan and
St{\"u}ker, Sebastian and
Wu, Dekai and
Mariani, Joseph and
Yvon, Francois},
booktitle = "Proceedings of the 17th International Conference on Spoken Language Translation",
month = jul,
year = "2020",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2020.iwslt-1.10",
doi = "10.18653/v1/2020.iwslt-1.10",
pages = "95--102",
abstract = "This paper describes the University of Helsinki Language Technology group{'}s participation in the IWSLT 2020 offline speech translation task, addressing the translation of English audio into German text. In line with this year{'}s task objective, we train both cascade and end-to-end systems for spoken language translation. We opt for an end-to-end multitasking architecture with shared internal representations and a cascade approach that follows a standard procedure consisting of ASR, correction, and MT stages. We also describe the experiments that served as a basis for the submitted systems. Our experiments reveal that multitasking training with shared internal representations is not only possible but allows for knowledge-transfer across modalities.",
}
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<abstract>This paper describes the University of Helsinki Language Technology group’s participation in the IWSLT 2020 offline speech translation task, addressing the translation of English audio into German text. In line with this year’s task objective, we train both cascade and end-to-end systems for spoken language translation. We opt for an end-to-end multitasking architecture with shared internal representations and a cascade approach that follows a standard procedure consisting of ASR, correction, and MT stages. We also describe the experiments that served as a basis for the submitted systems. Our experiments reveal that multitasking training with shared internal representations is not only possible but allows for knowledge-transfer across modalities.</abstract>
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%0 Conference Proceedings
%T The University of Helsinki Submission to the IWSLT2020 Offline SpeechTranslation Task
%A Vázquez, Raúl
%A Aulamo, Mikko
%A Sulubacak, Umut
%A Tiedemann, Jörg
%Y Federico, Marcello
%Y Waibel, Alex
%Y Knight, Kevin
%Y Nakamura, Satoshi
%Y Ney, Hermann
%Y Niehues, Jan
%Y Stüker, Sebastian
%Y Wu, Dekai
%Y Mariani, Joseph
%Y Yvon, Francois
%S Proceedings of the 17th International Conference on Spoken Language Translation
%D 2020
%8 July
%I Association for Computational Linguistics
%C Online
%F vazquez-etal-2020-university
%X This paper describes the University of Helsinki Language Technology group’s participation in the IWSLT 2020 offline speech translation task, addressing the translation of English audio into German text. In line with this year’s task objective, we train both cascade and end-to-end systems for spoken language translation. We opt for an end-to-end multitasking architecture with shared internal representations and a cascade approach that follows a standard procedure consisting of ASR, correction, and MT stages. We also describe the experiments that served as a basis for the submitted systems. Our experiments reveal that multitasking training with shared internal representations is not only possible but allows for knowledge-transfer across modalities.
%R 10.18653/v1/2020.iwslt-1.10
%U https://aclanthology.org/2020.iwslt-1.10
%U https://doi.org/10.18653/v1/2020.iwslt-1.10
%P 95-102
Markdown (Informal)
[The University of Helsinki Submission to the IWSLT2020 Offline SpeechTranslation Task](https://aclanthology.org/2020.iwslt-1.10) (Vázquez et al., IWSLT 2020)
ACL