@inproceedings{williams-etal-2023-um,
title = "{UM}-{DFKI} {M}altese Speech Translation",
author = {Williams, Aiden and
Abela, Kurt and
Kumar, Rishu and
B{\"a}r, Martin and
Billinghurst, Hannah and
Micallef, Kurt and
Mozib Samin, Ahnaf and
DeMarco, Andrea and
van der Plas, Lonneke and
Borg, Claudia},
editor = "Salesky, Elizabeth and
Federico, Marcello and
Carpuat, Marine",
booktitle = "Proceedings of the 20th International Conference on Spoken Language Translation (IWSLT 2023)",
month = jul,
year = "2023",
address = "Toronto, Canada (in-person and online)",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2023.iwslt-1.41",
doi = "10.18653/v1/2023.iwslt-1.41",
pages = "433--441",
abstract = "For the 2023 IWSLT Maltese Speech Translation Task, UM-DFKI jointly presents a cascade solution which achieves 0.6 BLEU. While this is the first time that a Maltese speech translation task has been released by IWSLT, this paper explores previous solutions for other speech translation tasks, focusing primarily on low-resource scenarios. Moreover, we present our method of fine-tuning XLS-R models for Maltese ASR using a collection of multi-lingual speech corpora as well as the fine-tuning of the mBART model for Maltese to English machine translation.",
}
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<abstract>For the 2023 IWSLT Maltese Speech Translation Task, UM-DFKI jointly presents a cascade solution which achieves 0.6 BLEU. While this is the first time that a Maltese speech translation task has been released by IWSLT, this paper explores previous solutions for other speech translation tasks, focusing primarily on low-resource scenarios. Moreover, we present our method of fine-tuning XLS-R models for Maltese ASR using a collection of multi-lingual speech corpora as well as the fine-tuning of the mBART model for Maltese to English machine translation.</abstract>
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%0 Conference Proceedings
%T UM-DFKI Maltese Speech Translation
%A Williams, Aiden
%A Abela, Kurt
%A Kumar, Rishu
%A Bär, Martin
%A Billinghurst, Hannah
%A Micallef, Kurt
%A Mozib Samin, Ahnaf
%A DeMarco, Andrea
%A van der Plas, Lonneke
%A Borg, Claudia
%Y Salesky, Elizabeth
%Y Federico, Marcello
%Y Carpuat, Marine
%S Proceedings of the 20th International Conference on Spoken Language Translation (IWSLT 2023)
%D 2023
%8 July
%I Association for Computational Linguistics
%C Toronto, Canada (in-person and online)
%F williams-etal-2023-um
%X For the 2023 IWSLT Maltese Speech Translation Task, UM-DFKI jointly presents a cascade solution which achieves 0.6 BLEU. While this is the first time that a Maltese speech translation task has been released by IWSLT, this paper explores previous solutions for other speech translation tasks, focusing primarily on low-resource scenarios. Moreover, we present our method of fine-tuning XLS-R models for Maltese ASR using a collection of multi-lingual speech corpora as well as the fine-tuning of the mBART model for Maltese to English machine translation.
%R 10.18653/v1/2023.iwslt-1.41
%U https://aclanthology.org/2023.iwslt-1.41
%U https://doi.org/10.18653/v1/2023.iwslt-1.41
%P 433-441
Markdown (Informal)
[UM-DFKI Maltese Speech Translation](https://aclanthology.org/2023.iwslt-1.41) (Williams et al., IWSLT 2023)
ACL
- Aiden Williams, Kurt Abela, Rishu Kumar, Martin Bär, Hannah Billinghurst, Kurt Micallef, Ahnaf Mozib Samin, Andrea DeMarco, Lonneke van der Plas, and Claudia Borg. 2023. UM-DFKI Maltese Speech Translation. In Proceedings of the 20th International Conference on Spoken Language Translation (IWSLT 2023), pages 433–441, Toronto, Canada (in-person and online). Association for Computational Linguistics.