Papers by Mucheol Kim

1 papers
Action-Concentrated Embedding Framework: This Is Your Captain Sign-tokening (2024.lrec-main)

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Challenge: ACE is a new sign token embedding framework that tracks a signer’s actions based on human posture estimation and captures the token embeds using a short-time Fourier transform.
Approach: They propose a novel sign token embedding framework that tracks a signer’s actions based on human posture estimation and a dedicated notation system tailored for sign language.
Outcome: The proposed framework outperforms previous studies in translation performance against a disaster sign language dataset and improves by up to 5.79% for BLEU-4 and 5.46% for ROUGE-L metric.

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