@inproceedings{pham-etal-2020-kits,
title = "{KIT}{'}s {IWSLT} 2020 {SLT} Translation System",
author = {Pham, Ngoc-Quan and
Schneider, Felix and
Nguyen, Tuan-Nam and
Ha, Thanh-Le and
Nguyen, Thai Son and
Awiszus, Maximilian and
St{\"u}ker, Sebastian and
Waibel, Alexander},
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-1.4",
doi = "10.18653/v1/2020.iwslt-1.4",
pages = "55--61",
abstract = "This paper describes KIT{'}s submissions to the IWSLT2020 Speech Translation evaluation campaign. We first participate in the simultaneous translation task, in which our simultaneous models are Transformer based and can be efficiently trained to obtain low latency with minimized compromise in quality. On the offline speech translation task, we applied our new Speech Transformer architecture to end-to-end speech translation. The obtained model can provide translation quality which is competitive to a complicated cascade. The latter still has the upper hand, thanks to the ability to transparently access to the transcription, and resegment the inputs to avoid fragmentation.",
}
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<abstract>This paper describes KIT’s submissions to the IWSLT2020 Speech Translation evaluation campaign. We first participate in the simultaneous translation task, in which our simultaneous models are Transformer based and can be efficiently trained to obtain low latency with minimized compromise in quality. On the offline speech translation task, we applied our new Speech Transformer architecture to end-to-end speech translation. The obtained model can provide translation quality which is competitive to a complicated cascade. The latter still has the upper hand, thanks to the ability to transparently access to the transcription, and resegment the inputs to avoid fragmentation.</abstract>
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%0 Conference Proceedings
%T KIT’s IWSLT 2020 SLT Translation System
%A Pham, Ngoc-Quan
%A Schneider, Felix
%A Nguyen, Tuan-Nam
%A Ha, Thanh-Le
%A Nguyen, Thai Son
%A Awiszus, Maximilian
%A Stüker, Sebastian
%A Waibel, Alexander
%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 pham-etal-2020-kits
%X This paper describes KIT’s submissions to the IWSLT2020 Speech Translation evaluation campaign. We first participate in the simultaneous translation task, in which our simultaneous models are Transformer based and can be efficiently trained to obtain low latency with minimized compromise in quality. On the offline speech translation task, we applied our new Speech Transformer architecture to end-to-end speech translation. The obtained model can provide translation quality which is competitive to a complicated cascade. The latter still has the upper hand, thanks to the ability to transparently access to the transcription, and resegment the inputs to avoid fragmentation.
%R 10.18653/v1/2020.iwslt-1.4
%U https://aclanthology.org/2020.iwslt-1.4
%U https://doi.org/10.18653/v1/2020.iwslt-1.4
%P 55-61
Markdown (Informal)
[KIT’s IWSLT 2020 SLT Translation System](https://aclanthology.org/2020.iwslt-1.4) (Pham et al., IWSLT 2020)
ACL
- Ngoc-Quan Pham, Felix Schneider, Tuan-Nam Nguyen, Thanh-Le Ha, Thai Son Nguyen, Maximilian Awiszus, Sebastian Stüker, and Alexander Waibel. 2020. KIT’s IWSLT 2020 SLT Translation System. In Proceedings of the 17th International Conference on Spoken Language Translation, pages 55–61, Online. Association for Computational Linguistics.