@inproceedings{hernandez-mena-etal-2020-masri,
title = "{MASRI}-{HEADSET}: A {M}altese Corpus for Speech Recognition",
author = "Hernandez Mena, Carlos Daniel and
Gatt, Albert and
DeMarco, Andrea and
Borg, Claudia and
van der Plas, Lonneke and
Muscat, Amanda and
Padovani, Ian",
booktitle = "Proceedings of the 12th Language Resources and Evaluation Conference",
month = may,
year = "2020",
address = "Marseille, France",
publisher = "European Language Resources Association",
url = "https://aclanthology.org/2020.lrec-1.784",
pages = "6381--6388",
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.",
language = "English",
ISBN = "979-10-95546-34-4",
}
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<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.</abstract>
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%0 Conference Proceedings
%T MASRI-HEADSET: A Maltese Corpus for Speech Recognition
%A Hernandez Mena, Carlos Daniel
%A Gatt, Albert
%A DeMarco, Andrea
%A Borg, Claudia
%A van der Plas, Lonneke
%A Muscat, Amanda
%A Padovani, Ian
%S Proceedings of the 12th Language Resources and Evaluation Conference
%D 2020
%8 may
%I European Language Resources Association
%C Marseille, France
%@ 979-10-95546-34-4
%G English
%F hernandez-mena-etal-2020-masri
%X 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.
%U https://aclanthology.org/2020.lrec-1.784
%P 6381-6388
Markdown (Informal)
[MASRI-HEADSET: A Maltese Corpus for Speech Recognition](https://aclanthology.org/2020.lrec-1.784) (Hernandez Mena et al., LREC 2020)
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 12th Language Resources and Evaluation Conference, pages 6381–6388, Marseille, France. European Language Resources Association.