How Much Data Is Enough Data? A New Motion Capture Corpus for Probabilistic Sign Language Generation

Anna Klezovich; Johanna Mesch; Gustav Eje Henter; Jonas Beskow

doi:10.63317/5pmyrs7f9o33

How Much Data Is Enough Data? A New Motion Capture Corpus for Probabilistic Sign Language Generation

Anna Klezovich, Johanna Mesch, Gustav Eje Henter, Jonas Beskow

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Abstract

We present a new 4.1 hours long high-quality motion capture sign language dataset for Swedish Sign Language — STS Mocap v1. The dataset consists of high quality multimodal data: body tracked with markers, fingers tracked with Manus Quantum Metagloves, face tracked with iPhone LiveLink app in MetaHuman Animator mode, and corresponding textual sentence translation to spoken Swedish. With the help of this dataset, we show that four hours of motion capture data is enough for generative modeling of sign language conditioned on 2D pose. In comparison, training the same flow-matching model on only 30 minutes of this data, which is a common size for sign language motion capture datasets, shows a significant degradation in the quality of the synthesized data.

Anthology ID:: 2026.lrec-1.750
Volume:: Proceedings of the Fifteenth Language Resources and Evaluation Conference
Month:: May
Year:: 2026
Address:: Palma de Mallorca, Spain
Editors:: Stelios Piperidis, Núria Bel, Henk van den Heuvel, Nancy Ide, Simon Krek, Antonio Toral
Venue:: LREC
SIG:
Publisher:: ELRA Language Resource Association
Note:
Pages:: 9549–9558
Language:
External URL:: https://lrec.elra.info/lrec2026-main-750
DOI:: 10.63317/5pmyrs7f9o33
Bibkey:
Cite (ACL):: Anna Klezovich, Johanna Mesch, Gustav Eje Henter, and Jonas Beskow. 2026. How Much Data Is Enough Data? A New Motion Capture Corpus for Probabilistic Sign Language Generation. In Proceedings of the Fifteenth Language Resources and Evaluation Conference, pages 9549–9558, Palma de Mallorca, Spain. ELRA Language Resource Association.
Cite (Informal):: How Much Data Is Enough Data? A New Motion Capture Corpus for Probabilistic Sign Language Generation (Klezovich et al., LREC 2026)
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@inproceedings{klezovich-etal-2026-much,
    title = "How Much Data Is Enough Data? A New Motion Capture Corpus for Probabilistic Sign Language Generation",
    author = "Klezovich, Anna  and
      Mesch, Johanna  and
      Henter, Gustav Eje  and
      Beskow, Jonas",
    editor = "Piperidis, Stelios  and
      Bel, N{\'u}ria  and
      van den Heuvel, Henk  and
      Ide, Nancy  and
      Krek, Simon  and
      Toral, Antonio",
    booktitle = "Proceedings of the Fifteenth Language Resources and Evaluation Conference",
    month = may,
    year = "2026",
    address = "Palma de Mallorca, Spain",
    publisher = "ELRA Language Resource Association",
    url = "https://aclanthology.org/2026.lrec-1.750/",
    doi = "10.63317/5pmyrs7f9o33",
    pages = "9549--9558",
    abstract = "We present a new 4.1 hours long high-quality motion capture sign language dataset for Swedish Sign Language {---} STS Mocap v1. The dataset consists of high quality multimodal data: body tracked with markers, fingers tracked with Manus Quantum Metagloves, face tracked with iPhone LiveLink app in MetaHuman Animator mode, and corresponding textual sentence translation to spoken Swedish. With the help of this dataset, we show that four hours of motion capture data is enough for generative modeling of sign language conditioned on 2D pose. In comparison, training the same flow-matching model on only 30 minutes of this data, which is a common size for sign language motion capture datasets, shows a significant degradation in the quality of the synthesized data."
}

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%0 Conference Proceedings
%T How Much Data Is Enough Data? A New Motion Capture Corpus for Probabilistic Sign Language Generation
%A Klezovich, Anna
%A Mesch, Johanna
%A Henter, Gustav Eje
%A Beskow, Jonas
%Y Piperidis, Stelios
%Y Bel, Núria
%Y van den Heuvel, Henk
%Y Ide, Nancy
%Y Krek, Simon
%Y Toral, Antonio
%S Proceedings of the Fifteenth Language Resources and Evaluation Conference
%D 2026
%8 May
%I ELRA Language Resource Association
%C Palma de Mallorca, Spain
%F klezovich-etal-2026-much
%X We present a new 4.1 hours long high-quality motion capture sign language dataset for Swedish Sign Language — STS Mocap v1. The dataset consists of high quality multimodal data: body tracked with markers, fingers tracked with Manus Quantum Metagloves, face tracked with iPhone LiveLink app in MetaHuman Animator mode, and corresponding textual sentence translation to spoken Swedish. With the help of this dataset, we show that four hours of motion capture data is enough for generative modeling of sign language conditioned on 2D pose. In comparison, training the same flow-matching model on only 30 minutes of this data, which is a common size for sign language motion capture datasets, shows a significant degradation in the quality of the synthesized data.
%R 10.63317/5pmyrs7f9o33
%U https://aclanthology.org/2026.lrec-1.750/
%U https://doi.org/10.63317/5pmyrs7f9o33
%P 9549-9558

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Markdown (Informal)

[How Much Data Is Enough Data? A New Motion Capture Corpus for Probabilistic Sign Language Generation](https://aclanthology.org/2026.lrec-1.750/) (Klezovich et al., LREC 2026)

How Much Data Is Enough Data? A New Motion Capture Corpus for Probabilistic Sign Language Generation (Klezovich et al., LREC 2026)

ACL

Anna Klezovich, Johanna Mesch, Gustav Eje Henter, and Jonas Beskow. 2026. How Much Data Is Enough Data? A New Motion Capture Corpus for Probabilistic Sign Language Generation. In Proceedings of the Fifteenth Language Resources and Evaluation Conference, pages 9549–9558, Palma de Mallorca, Spain. ELRA Language Resource Association.