Andrea DeMarco


2023

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UM-DFKI Maltese Speech Translation
Aiden Williams | Kurt Abela | Rishu Kumar | Martin Bär | Hannah Billinghurst | Kurt Micallef | Ahnaf Mozib Samin | Andrea DeMarco | Lonneke van der Plas | Claudia Borg
Proceedings of the 20th International Conference on Spoken Language Translation (IWSLT 2023)

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.

2020

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MASRI-HEADSET: A Maltese Corpus for Speech Recognition
Carlos Daniel Hernandez Mena | Albert Gatt | Andrea DeMarco | Claudia Borg | Lonneke van der Plas | Amanda Muscat | Ian Padovani
Proceedings of the Twelfth Language Resources and Evaluation Conference

Maltese, the national language of Malta, is spoken by approximately 500,000 people. Speech processing for Maltese is still in its early stages of development. In this paper, we present the first spoken Maltese corpus designed purposely for Automatic Speech Recognition (ASR). The MASRI-HEADSET corpus was developed by the MASRI project at the University of Malta. It consists of 8 hours of speech paired with text, recorded by using short text snippets in a laboratory environment. The speakers were recruited from different geographical locations all over the Maltese islands, and were roughly evenly distributed by gender. This paper also presents some initial results achieved in baseline experiments for Maltese ASR using Sphinx and Kaldi. The MASRI HEADSET Corpus is publicly available for research/academic purposes.