Enhancing Portuguese Variety Identification with Cross-Domain Approaches
This work addresses the limited applicability of Portuguese NLP models outside Brazil, though it is incremental as it builds on existing transformer methods for a specific domain.
The paper tackled the problem of linguistic bias in Portuguese language models due to the predominance of Brazilian Portuguese corpora by developing a cross-domain language variety identifier to discriminate between European and Brazilian Portuguese, resulting in the creation of the PtBrVarId corpus and open-sourced transformer-based classifiers.
Recent advances in natural language processing have raised expectations for generative models to produce coherent text across diverse language varieties. In the particular case of the Portuguese language, the predominance of Brazilian Portuguese corpora online introduces linguistic biases in these models, limiting their applicability outside of Brazil. To address this gap and promote the creation of European Portuguese resources, we developed a cross-domain language variety identifier (LVI) to discriminate between European and Brazilian Portuguese. Motivated by the findings of our literature review, we compiled the PtBrVarId corpus, a cross-domain LVI dataset, and study the effectiveness of transformer-based LVI classifiers for cross-domain scenarios. Although this research focuses on two Portuguese varieties, our contribution can be extended to other varieties and languages. We open source the code, corpus, and models to foster further research in this task.