@inproceedings{abela-etal-2024-uom,
title = "{UOM}-Constrained {IWSLT} 2024 Shared Task Submission - {M}altese Speech Translation",
author = "Abela, Kurt and
Abdur Razzaq Riyadh, Md and
Galea, Melanie and
Busuttil, Alana and
Kovalev, Roman and
Williams, Aiden and
Borg, Claudia",
editor = "Salesky, Elizabeth and
Federico, Marcello and
Carpuat, Marine",
booktitle = "Proceedings of the 21st International Conference on Spoken Language Translation (IWSLT 2024)",
month = aug,
year = "2024",
address = "Bangkok, Thailand (in-person and online)",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2024.iwslt-1.15/",
doi = "10.18653/v1/2024.iwslt-1.15",
pages = "108--113",
abstract = "This paper presents our IWSLT-2024 shared task submission on the low-resource track. This submission forms part of the constrained setup; implying limited data for training. Following the introduction, this paper consists of a literature review defining previous approaches to speech translation, as well as their application to Maltese, followed by the defined methodology, evaluation and results, and the conclusion. A cascaded submission on the Maltese to English language pair is presented; consisting of a pipeline containing: a DeepSpeech 1 Automatic Speech Recognition (ASR) system, a KenLM model to optimise the transcriptions, and finally an LSTM machine translation model. The submission achieves a 0.5 BLEU score on the overall test set, and the ASR system achieves a word error rate of 97.15{\%}. Our code is made publicly available."
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%0 Conference Proceedings
%T UOM-Constrained IWSLT 2024 Shared Task Submission - Maltese Speech Translation
%A Abela, Kurt
%A Abdur Razzaq Riyadh, Md
%A Galea, Melanie
%A Busuttil, Alana
%A Kovalev, Roman
%A Williams, Aiden
%A Borg, Claudia
%Y Salesky, Elizabeth
%Y Federico, Marcello
%Y Carpuat, Marine
%S Proceedings of the 21st International Conference on Spoken Language Translation (IWSLT 2024)
%D 2024
%8 August
%I Association for Computational Linguistics
%C Bangkok, Thailand (in-person and online)
%F abela-etal-2024-uom
%X This paper presents our IWSLT-2024 shared task submission on the low-resource track. This submission forms part of the constrained setup; implying limited data for training. Following the introduction, this paper consists of a literature review defining previous approaches to speech translation, as well as their application to Maltese, followed by the defined methodology, evaluation and results, and the conclusion. A cascaded submission on the Maltese to English language pair is presented; consisting of a pipeline containing: a DeepSpeech 1 Automatic Speech Recognition (ASR) system, a KenLM model to optimise the transcriptions, and finally an LSTM machine translation model. The submission achieves a 0.5 BLEU score on the overall test set, and the ASR system achieves a word error rate of 97.15%. Our code is made publicly available.
%R 10.18653/v1/2024.iwslt-1.15
%U https://aclanthology.org/2024.iwslt-1.15/
%U https://doi.org/10.18653/v1/2024.iwslt-1.15
%P 108-113
Markdown (Informal)
[UOM-Constrained IWSLT 2024 Shared Task Submission - Maltese Speech Translation](https://aclanthology.org/2024.iwslt-1.15/) (Abela et al., IWSLT 2024)
ACL
- Kurt Abela, Md Abdur Razzaq Riyadh, Melanie Galea, Alana Busuttil, Roman Kovalev, Aiden Williams, and Claudia Borg. 2024. UOM-Constrained IWSLT 2024 Shared Task Submission - Maltese Speech Translation. In Proceedings of the 21st International Conference on Spoken Language Translation (IWSLT 2024), pages 108–113, Bangkok, Thailand (in-person and online). Association for Computational Linguistics.