Year: 2025
Type: conference-paper
Abstract: This paper introduces a preprocessing pipeline for keypoints extracted using MediaPipe, aiming to improve pose annotation consistency in sign language datasets.We evaluate its effectiveness using a sign similarity task based on phonological features, without relying on gloss annotations.Similarity is measured using Dynamic Time Warping (DTW) across videos from sign language dictionaries.Although such similarity analyses can support various sign language processing applications -such as lexical search, clustering, and data enrichment -the main contribution of this work is to standardise pose features across heterogeneous sources, including different signers and backgrounds.Experiments on two dictionary datasets show that our pipeline significantly improves similarity measurements, with promising benefits for other sign language processing tasks.
Authors: Kehina Manseri, Sam Bigeard, Slim Ouni
Language: English
Subfield: Human-Computer Interaction
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
OpenAlex ID: W4414628793