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.

In this paper we describe STS-korpus, a web corpus tool for Swedish Sign Language (STS) which we have built during the past year, and which is now publicly available on the internet. STS-korpus uses the data of Swedish Sign Language Corpus (SSLC) and is primarily intended for teachers and students of sign language. As such it is created to be simple and user-friendly with no download or setup required. The user interface allows for searching – with search results displayed as a simple concordance – and viewing of videos with annotations. Each annotation also provides additional data and links to the corresponding entry in the online Swedish Sign Language Dictionary. We describe the corpus, its appearance and search syntax, as well as more advanced features like access control and dynamic content. Finally we say a word or two about the role we hope it will play in the classroom, and something about the development process and the software used. STS-korpus is available here: https://teckensprakskorpus.su.se