Enhancing Accessible Communication: from European Portuguese to Portuguese Sign Language
Submission Type: Regular Short Paper
Submission Track: Resources and Evaluation
Keywords: Portuguese Sign Language, Machine Translation, Computational Linguistics, Natural Language Processing, Deep Learning
TL;DR: The paper presents rule-based and neural models for translating European Portuguese to Portuguese Sign Language, yielding improved results and a new corpus and a gold collection for future evaluations.
Abstract: Portuguese Sign Language (LGP) is the official language in deaf education in Portugal. Current approaches in developing a translation system between European Portuguese and LGP rely on hand-crafted rules. In this paper, we present a fully automatic corpora-driven rule-based machine translation system between European Portuguese and LGP glosses, and also two neural machine translation models. We also contribute with the LGP-5-Domain corpus, composed of five different text domains, built with the help of our rule-based system, and used to train the neural models. In addition, we provide a gold collection, annotated by LGP experts, that can be used for future evaluations. Compared with the only similar available translation system, PE2LGP, results are always improved with the new rule-based model, which competes for the highest scores with one of the neural models.
Submission Number: 3991
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