Neural based machine translation from Catalan Sign Language glosses to written catalan

Chabaud, Luka

Neural based machine translation from Catalan Sign Language glosses to written catalan

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Citation

Chabaud, L. Neural based machine translation from Catalan Sign Language glosses to written catalan. 2024. handle: http://hdl.handle.net/10230/61313

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Abstract

This thesis had two objectives: the first one was to experiment with an alternative method to statistical machine translation, which had already been researched for Catalan Sign Language (LSC), using state-of-the-art Neural Networks. More precisely, this work focuses on the yet unexplored translation task from LSC glosses to written Catalan, finding the best possible neural architecture by searching for the best hyperparameter values. The second objective was to apply existing data augmentation techniques for Sign Languages, also developing specific LSC rules, based on its grammar, in order to create a parallel corpus of synthetic data. We then used this augmented data to enhance the training of the models, achieving significant improvements over a baseline without the need of new labeled data.