Tradutor: Building a Variety Specific Translation Model

Language models have become foundational to many widely used systems. However, these seemingly advantageous models are double-edged swords. While they excel in tasks related to resource-rich languages like English, they often lose the fine nuances of language forms, dialects, and varieties that are inherent to languages spoken in multiple regions of the world. Languages like European Portuguese are neglected in favor of their more popular counterpart, Brazilian Portuguese, leading to suboptimal performance in various linguistic tasks. To address this gap, we introduce the first open-source translation model specifically tailored for European Portuguese, along with a novel dataset specifically designed for this task. Results from automatic evaluations on two benchmark datasets demonstrate that our best model surpasses existing open-source translation systems for Portuguese and approaches the performance of industry-leading closed-source systems for European Portuguese. By making our dataset, models, and code publicly available, we aim to support and encourage further research, fostering advancements in the representation of underrepresented language varieties.

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Publication Details

Journal
Proceedings of the AAAI Conference on Artificial Intelligence
Published
2025-04-11
DOI
https://doi.org/10.1609/aaai.v39i24.34704
Primary Topic
Translation Studies and Practices
Type
article
Field-Weighted Citation Impact
0.00

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article

Tradutor: Building a Variety Specific Translation Model

Alí­pio Jorge, Satya Almasian, Hugo Sousa, Ricardo Campos
Proceedings of the AAAI Conference on Artificial Intelligence
Translation Studies and Practices
article

Tradutor: Building a Variety Specific Translation Model

Alí­pio Jorge, Satya Almasian, Hugo Sousa, Ricardo Campos
article en

Abstract

Language models have become foundational to many widely used systems. However, these seemingly advantageous models are double-edged swords. While they excel in tasks related to resource-rich languages like English, they often lose the fine nuances of language forms, dialects, and varieties that are inherent to languages spoken in multiple regions of the world. Languages like European Portuguese are neglected in favor of their more popular counterpart, Brazilian Portuguese, leading to suboptimal performance in various linguistic tasks. To address this gap, we introduce the first open-source translation model specifically tailored for European Portuguese, along with a novel dataset specifically designed for this task. Results from automatic evaluations on two benchmark datasets demonstrate that our best model surpasses existing open-source translation systems for Portuguese and approaches the performance of industry-leading closed-source systems for European Portuguese. By making our dataset, models, and code publicly available, we aim to support and encourage further research, fostering advancements in the representation of underrepresented language varieties.

Proceedings of the AAAI Conference on Artificial IntelligenceVol. 39(24)
University of Beira Interior (PT), Heidelberg University (DE), INESC TEC (PT)
Fundação para a Ciência e a Tecnologia
Openalex Percentile: Top 89%
Translation Studies and Practices
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Tradutor: Building a Variety Specific Translation Model — Alí­pio Jorge, Satya Almasian, et al. · Proceedings of the AAAI Conference on Artificial Intelligence (2025) | TGRS Research Map | TGRS