@inproceedings{renner-etal-2026-effect,
title = "Effect of Data Augmentation with Multi-View Perspectives of Signers on the {DGS}-Fabeln-1 Dataset",
author = "Renner, Fabian and
Withanage Don, Daksitha and
Andre, Elisabeth and
Luna Jimenez, Cristina",
editor = "Efthimiou, Eleni and
Fotinea, Stavroula-Evita and
Hanke, Thomas and
Hochgesang, Julie A. and
Mesch, Johanna and
Schulder, Marc",
booktitle = "Proceedings of the {LREC} 2026 12th Workshop on the Representation and Processing of Sign Languages: Language in Motion",
month = may,
year = "2026",
address = "Palma, Mallorca (Spain)",
publisher = "ELRA Language Resources Association (ELRA)",
url = "https://aclanthology.org/2026.signlang-1.44/",
doi = "10.63317/2zrdptjrx3pa",
pages = "429--437",
abstract = "Sign languages constitute the principal form of communication for deaf communities across the globe. Nevertheless, the development of reliable Continuous Sign Language Translation (CSLT) systems is constrained by the lack of sufficient data and models able to handle spatio-temporal information. In this article, we explore the effect of adding multiview perspectives of the signer to the training set as data augmentation using the UniSign framework for the DGS-Fabeln-1 dataset. Our results reveal that increasing dataset size and using multiple camera perspectives significantly improve performance, with the best configurations achieving BLEU-4 scores of 4.20{\%}. These results provide a competitive baseline for the DGS-Fabeln-1 dataset and guidance for further optimizations of CSLT systems."
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<abstract>Sign languages constitute the principal form of communication for deaf communities across the globe. Nevertheless, the development of reliable Continuous Sign Language Translation (CSLT) systems is constrained by the lack of sufficient data and models able to handle spatio-temporal information. In this article, we explore the effect of adding multiview perspectives of the signer to the training set as data augmentation using the UniSign framework for the DGS-Fabeln-1 dataset. Our results reveal that increasing dataset size and using multiple camera perspectives significantly improve performance, with the best configurations achieving BLEU-4 scores of 4.20%. These results provide a competitive baseline for the DGS-Fabeln-1 dataset and guidance for further optimizations of CSLT systems.</abstract>
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%0 Conference Proceedings
%T Effect of Data Augmentation with Multi-View Perspectives of Signers on the DGS-Fabeln-1 Dataset
%A Renner, Fabian
%A Withanage Don, Daksitha
%A Andre, Elisabeth
%A Luna Jimenez, Cristina
%Y Efthimiou, Eleni
%Y Fotinea, Stavroula-Evita
%Y Hanke, Thomas
%Y Hochgesang, Julie A.
%Y Mesch, Johanna
%Y Schulder, Marc
%S Proceedings of the LREC 2026 12th Workshop on the Representation and Processing of Sign Languages: Language in Motion
%D 2026
%8 May
%I ELRA Language Resources Association (ELRA)
%C Palma, Mallorca (Spain)
%F renner-etal-2026-effect
%X Sign languages constitute the principal form of communication for deaf communities across the globe. Nevertheless, the development of reliable Continuous Sign Language Translation (CSLT) systems is constrained by the lack of sufficient data and models able to handle spatio-temporal information. In this article, we explore the effect of adding multiview perspectives of the signer to the training set as data augmentation using the UniSign framework for the DGS-Fabeln-1 dataset. Our results reveal that increasing dataset size and using multiple camera perspectives significantly improve performance, with the best configurations achieving BLEU-4 scores of 4.20%. These results provide a competitive baseline for the DGS-Fabeln-1 dataset and guidance for further optimizations of CSLT systems.
%R 10.63317/2zrdptjrx3pa
%U https://aclanthology.org/2026.signlang-1.44/
%U https://doi.org/10.63317/2zrdptjrx3pa
%P 429-437
Markdown (Informal)
[Effect of Data Augmentation with Multi-View Perspectives of Signers on the DGS-Fabeln-1 Dataset](https://aclanthology.org/2026.signlang-1.44/) (Renner et al., SignLang 2026)
ACL