no code implementations • TDLE (LREC) 2022 • Marko Tadić, Daša Farkaš, Matea Filko, Artūrs Vasiļevskis, Andrejs Vasiļjevs, Jānis Ziediņš, Željka Motika, Mark Fishel, Hrafn Loftsson, Jón Guðnason, Claudia Borg, Keith Cortis, Judie Attard, Donatienne Spiteri
This article presents the work in progress on the collaborative project of several European countries to develop National Language Technology Platform (NLTP).
no code implementations • EAMT 2022 • Artūrs Vasiļevskis, Jānis Ziediņš, Marko Tadić, None Željka Motika, Mark Fishel, Hrafn Loftsson, Jón Gu, Claudia Borg, Keith Cortis, Judie Attard, Donatienne Spiteri
The work in progress on the CEF Action National Language Technology Platform (NLTP) is presented.
no code implementations • 30 Jan 2024 • Kurt Micallef, Nizar Habash, Claudia Borg, Fadhl Eryani, Houda Bouamor
Although multilingual language models exhibit impressive cross-lingual transfer capabilities on unseen languages, the performance on downstream tasks is impacted when there is a script disparity with the languages used in the multilingual model's pre-training data.
no code implementations • PVLAM (LREC) 2022 • Marc Tanti, Shaun Abdilla, Adrian Muscat, Claudia Borg, Reuben A. Farrugia, Albert Gatt
To encourage the development of more human-focused descriptions, we developed a new data set of facial descriptions based on the CelebA image data set.
1 code implementation • DeepLo 2022 • Kurt Micallef, Albert Gatt, Marc Tanti, Lonneke van der Plas, Claudia Borg
We also present a newly created corpus for Maltese, and determine the effect that the pre-training data size and domain have on the downstream performance.
no code implementations • 15 Nov 2021 • Andrea DeMarco, Carlos Mena, Albert Gatt, Claudia Borg, Aiden Williams, Lonneke van der Plas
Recent years have seen an increased interest in the computational speech processing of Maltese, but resources remain sparse.
1 code implementation • EMNLP (BlackboxNLP) 2021 • Marc Tanti, Lonneke van der Plas, Claudia Borg, Albert Gatt
Recent work has shown evidence that the knowledge acquired by multilingual BERT (mBERT) has two components: a language-specific and a language-neutral one.
no code implementations • LREC 2020 • Carlos Mena, Albert Gatt, Andrea DeMarco, Claudia Borg, Lonneke van der Plas, Amanda Muscat, Ian Padovani
Maltese, the national language of Malta, is spoken by approximately 500, 000 people.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +1
no code implementations • LREC 2020 • Lionel Nicolas, Verena Lyding, Claudia Borg, Corina Forascu, Kar{\"e}n Fort, Katerina Zdravkova, Iztok Kosem, Jaka {\v{C}}ibej, {\v{S}}pela Arhar Holdt, Alice Millour, Alex K{\"o}nig, er, Christos Rodosthenous, Federico Sangati, Umair ul Hassan, Anisia Katinskaia, Anabela Barreiro, Lavinia Aparaschivei, Yaakov HaCohen-Kerner
We introduce in this paper a generic approach to combine implicit crowdsourcing and language learning in order to mass-produce language resources (LRs) for any language for which a crowd of language learners can be involved.
no code implementations • WS 2019 • Ronald Cardenas, Claudia Borg, Daniel Zeman
This paper presents the submission by the Charles University-University of Malta team to the SIGMORPHON 2019 Shared Task on Morphological Analysis and Lemmatization in context.
1 code implementation • LREC 2018 • Albert Gatt, Marc Tanti, Adrian Muscat, Patrizia Paggio, Reuben A. Farrugia, Claudia Borg, Kenneth P. Camilleri, Mike Rosner, Lonneke van der Plas
To gain a better understanding of the variation we find in face description and the possible issues that this may raise, we also conducted an annotation study on a subset of the corpus.
no code implementations • WS 2017 • Claudia Borg, Albert Gatt
In particular, we analyse a dataset of morphologically related word clusters to evaluate the difference in results for concatenative and nonconcatenative clusters.
no code implementations • LREC 2014 • Claudia Borg, Albert Gatt
The automatic discovery and clustering of morphologically related words is an important problem with several practical applications.