Papers by Carme Armentano-Oller
Building a Data Infrastructure for a Mid-Resource Language: The Case of Catalan (2024.lrec-main)
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Aitor Gonzalez-Agirre, Montserrat Marimon, Carlos Rodriguez-Penagos, Javier Aula-Blasco, Irene Baucells, Carme Armentano-Oller, Jorge Palomar-Giner, Baybars Kulebi, Marta Villegas
| Challenge: | Aina Project aims to provide Catalan with the resources needed to keep its relevance in AI/NLP applications. |
| Approach: | They propose a set of strategies to consider when improving technology support for a mid- or low-resource language . they propose annotated datasets and a framework to make models ready to use . |
| Outcome: | The Aina Project aims to provide Catalan with the necessary resources to keep its relevance in AI/NLP-related industry and research. |
Becoming a High-Resource Language in Speech: The Catalan Case in the Common Voice Corpus (2024.lrec-main)
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| Challenge: | a project to create a publicly available voice dataset for speech recognition systems in Catalan is a multifaceted challenge. |
| Approach: | They propose to create a publicly available voice dataset for future speech technologies in Catalan using the Mozilla Common Voice crowd-sourcing platform. |
| Outcome: | The proposed dataset shows that Catalan ranks as the most prominent language in the corpus. |
Are Multilingual Models the Best Choice for Moderately Under-resourced Languages? A Comprehensive Assessment for Catalan (2021.findings-acl)
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Jordi Armengol-Estapé, Casimiro Pio Carrino, Carlos Rodriguez-Penagos, Ona de Gibert Bonet, Carme Armentano-Oller, Aitor Gonzalez-Agirre, Maite Melero, Marta Villegas
| Challenge: | Multilingual language models have been a crucial breakthrough for under-resourced languages . however, the superiority of language-specific models has already been proven for underresourced ones . |
| Approach: | They propose to build a monolingual monolingual model that is comparable to state-of-the-art large multilingual models. |
| Outcome: | The proposed model consistently outperforms state-of-the-art models across tasks and settings. |