Jun Woo Lee

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2022

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KoSign Sign Language Translation Project: Introducing The NIASL2021 Dataset
Mathew Huerta-Enochian | Du Hui Lee | Hye Jin Myung | Kang Suk Byun | Jun Woo Lee
Proceedings of the 7th International Workshop on Sign Language Translation and Avatar Technology: The Junction of the Visual and the Textual: Challenges and Perspectives

We introduce a new sign language production (SLP) and sign language translation (SLT) dataset, NIASL2021, consisting of 201,026 Korean-KSL data pairs. KSL translations of Korean source texts are represented in three formats: video recordings, keypoint position data, and time-aligned gloss annotations for each hand (using a 7,989 sign vocabulary) and for eight different non-manual signals (NMS). We evaluated our sign language elicitation methodology and found that text-based prompting had a negative effect on translation quality in terms of naturalness and comprehension. We recommend distilling text into a visual medium before translating into sign language or adding a prompt-blind review step to text-based translation methodologies.
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