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Authors: João Gondim ; Daniela Barreiro Claro and Marlo Souza

Affiliation: FORMAS Research Group, Institute of Computing, Federal University of Bahia, Av. Milton Santos, s/n, PAF2., Campus de Ondina, Salvador, Bahia, Brazil

Keyword(s): Image Captioning, Natural Language Processing, Machine Translation.

Abstract: Automatic describing an image comprehends the representation from the scene elements to generate a concise natural language description. Few resources, particularly annotated datasets for the Portuguese language, discourage the development of new methods in languages other than English. Thus, we propose a new image captioning method for the Portuguese language. We provide an analysis empowered by an encoder-decoder model with an attention mechanism when employing a multimodal dataset translated into Portuguese. Our findings suggest that: 1) the original and translated datasets are pretty similar considering the measure achievements; 2) the translation approach includes some dirty sentence formulations that disturb our model for the Portuguese language.

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Paper citation in several formats:
Gondim, J.; Claro, D. and Souza, M. (2022). Towards Image Captioning for the Portuguese Language: Evaluation on a Translated Dataset. In Proceedings of the 24th International Conference on Enterprise Information Systems - Volume 1: ICEIS; ISBN 978-989-758-569-2; ISSN 2184-4992, SciTePress, pages 384-393. DOI: 10.5220/0011080000003179

@conference{iceis22,
author={João Gondim. and Daniela Barreiro Claro. and Marlo Souza.},
title={Towards Image Captioning for the Portuguese Language: Evaluation on a Translated Dataset},
booktitle={Proceedings of the 24th International Conference on Enterprise Information Systems - Volume 1: ICEIS},
year={2022},
pages={384-393},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011080000003179},
isbn={978-989-758-569-2},
issn={2184-4992},
}

TY - CONF

JO - Proceedings of the 24th International Conference on Enterprise Information Systems - Volume 1: ICEIS
TI - Towards Image Captioning for the Portuguese Language: Evaluation on a Translated Dataset
SN - 978-989-758-569-2
IS - 2184-4992
AU - Gondim, J.
AU - Claro, D.
AU - Souza, M.
PY - 2022
SP - 384
EP - 393
DO - 10.5220/0011080000003179
PB - SciTePress