@inproceedings{loy-morgan-2026-hns2cf,
title = "{HNS}2{CF}: A Mapping Tool from {H}am{N}o{S}ys to {SL} {C}at{F}orm",
author = "Loy, Lisa and
Morgan, Hope E.",
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-1.30/",
doi = "10.63317/3m5m8sp4qe6j",
pages = "287--296",
abstract = "Over the past six decades, a variety of systems have been developed for representing sign language forms, from Stokoe Notation (Stokoe, 1960) to SignWriting (Sutton, 1999) and lexical database schemas. Each was designed with specific goals and applications, leading to a fragmented landscape of representations. To enable greater interoperability and data sharing among sign language users and researchers, we propose a robust approach to translating between notation systems. As a first step in this direction, we introduce a formal mapping framework between HamNoSys and the SL CatForm coding schema, describe its implementation, and present empirical evidence of its performance. An extensive evaluation of mapping mismatches revealed improvements to the mapping logic needed to further advance the HNS2CF mapping tool. However, the initial version of the system already achieves an overall accuracy of 76.7{\%} and an in-depth analysis reveals that many apparent mismatches stem from annotator disagreement rather than mapping errors, indicating that the tool{'}s actual accuracy is even higher. These results demonstrate the feasibility and promise of establishing mapping mechanisms across sign representation systems."
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<abstract>Over the past six decades, a variety of systems have been developed for representing sign language forms, from Stokoe Notation (Stokoe, 1960) to SignWriting (Sutton, 1999) and lexical database schemas. Each was designed with specific goals and applications, leading to a fragmented landscape of representations. To enable greater interoperability and data sharing among sign language users and researchers, we propose a robust approach to translating between notation systems. As a first step in this direction, we introduce a formal mapping framework between HamNoSys and the SL CatForm coding schema, describe its implementation, and present empirical evidence of its performance. An extensive evaluation of mapping mismatches revealed improvements to the mapping logic needed to further advance the HNS2CF mapping tool. However, the initial version of the system already achieves an overall accuracy of 76.7% and an in-depth analysis reveals that many apparent mismatches stem from annotator disagreement rather than mapping errors, indicating that the tool’s actual accuracy is even higher. These results demonstrate the feasibility and promise of establishing mapping mechanisms across sign representation systems.</abstract>
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%0 Conference Proceedings
%T HNS2CF: A Mapping Tool from HamNoSys to SL CatForm
%A Loy, Lisa
%A Morgan, Hope E.
%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 loy-morgan-2026-hns2cf
%X Over the past six decades, a variety of systems have been developed for representing sign language forms, from Stokoe Notation (Stokoe, 1960) to SignWriting (Sutton, 1999) and lexical database schemas. Each was designed with specific goals and applications, leading to a fragmented landscape of representations. To enable greater interoperability and data sharing among sign language users and researchers, we propose a robust approach to translating between notation systems. As a first step in this direction, we introduce a formal mapping framework between HamNoSys and the SL CatForm coding schema, describe its implementation, and present empirical evidence of its performance. An extensive evaluation of mapping mismatches revealed improvements to the mapping logic needed to further advance the HNS2CF mapping tool. However, the initial version of the system already achieves an overall accuracy of 76.7% and an in-depth analysis reveals that many apparent mismatches stem from annotator disagreement rather than mapping errors, indicating that the tool’s actual accuracy is even higher. These results demonstrate the feasibility and promise of establishing mapping mechanisms across sign representation systems.
%R 10.63317/3m5m8sp4qe6j
%U https://aclanthology.org/2026.signlang-1.30/
%U https://doi.org/10.63317/3m5m8sp4qe6j
%P 287-296
Markdown (Informal)
[HNS2CF: A Mapping Tool from HamNoSys to SL CatForm](https://aclanthology.org/2026.signlang-1.30/) (Loy & Morgan, SignLang 2026)
ACL
- Lisa Loy and Hope E. Morgan. 2026. HNS2CF: A Mapping Tool from HamNoSys to SL CatForm. In Proceedings of the LREC 2026 12th Workshop on the Representation and Processing of Sign Languages: Language in Motion, pages 287–296, Palma, Mallorca (Spain). ELRA Language Resources Association (ELRA).