MASRI-HEADSET: A Maltese Corpus for Speech Recognition
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Abstract (arXiv)
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.
Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). First posted on arXiv 13 Aug 2020.
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Citing papers per year: 2021: 1; 2022: 0; 2023: 0; 2024: 2; 2025: 1.
4 papers.
- 2024From LLM to NMT: Advancing Low-Resource Machine Translation with Claudecited by 57
- 2024MOSEL: 950,000 Hours of Speech Data for Open-Source Speech Foundation Model Training on EU Languagescited by 13
- 2025EuroSpeech: A Multilingual Speech Corpuscited by 3
- 2021Analysis of Data Augmentation Methods for Low-Resource Maltese ASRcited by 0
- 2025EuroSpeech: A Multilingual Speech Corpus1 Oct 2025
- 2024MOSEL: 950,000 Hours of Speech Data for Open-Source Speech Foundation Model Training on EU Languages1 Oct 2024
- 2024From LLM to NMT: Advancing Low-Resource Machine Translation with Claude22 Apr 2024
- 2021Analysis of Data Augmentation Methods for Low-Resource Maltese ASR15 Nov 2021