Antonielle Martins

Gloss-to-Text Translation for Libras and Portuguese: Evaluating Pretrained and Fine-Tuned Encoder-Decoder Models

We evaluate encoder-decoder models for Gloss-to-Text translation from Brazilian Sign Language (Libras) glosses into Portuguese using a corpus derived from Libras-UFPel. The evaluated models are mT5-small, mT5-base, Flan-T5-base, and PTT5-v2-base. Experiments were conducted with 5-fold cross-validation and evaluated using BLEU and chrF. All models improved after supervised fine-tuning, with PTT5-v2-base achieving the best overall performance. The results suggest that Portuguese-specialized encoder-decoder models are a promising direction for Gloss-to-Text translation in low-resource settings.