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

Abstract
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.
Anthology ID:
2020.lrec-1.784
Volume:
Proceedings of the Twelfth Language Resources and Evaluation Conference
Month:
May
Year:
2020
Address:
Marseille, France
Venue:
LREC
SIG:
Publisher:
European Language Resources Association
Note:
Pages:
6381–6388
Language:
English
URL:
https://aclanthology.org/2020.lrec-1.784
DOI:
Bibkey:
Cite (ACL):
Carlos Daniel Hernandez Mena, Albert Gatt, Andrea DeMarco, Claudia Borg, Lonneke van der Plas, Amanda Muscat, and Ian Padovani. 2020. MASRI-HEADSET: A Maltese Corpus for Speech Recognition. In Proceedings of the Twelfth Language Resources and Evaluation Conference, pages 6381–6388, Marseille, France. European Language Resources Association.
Cite (Informal):
MASRI-HEADSET: A Maltese Corpus for Speech Recognition (Hernandez Mena et al., LREC 2020)
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PDF:
https://preview.aclanthology.org/ingestion-script-update/2020.lrec-1.784.pdf
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