2025 AACL AACL 2025

Cross-Linguistic Phonological Similarity Analysis in Sign Languages Using HamNoSys

Abstract

AbstractThis paper presents a cross-linguistic analysis of phonological similarity in sign languages using symbolic representations from the Hamburg Notation System (HamNoSys). We construct a dataset of 1000 signs each from British Sign Language (BSL), German Sign Language (DGS), French Sign Language (LSF), and Greek Sign Language (GSL), and compute pairwise phonological similarity using normalized edit distance over HamNoSys strings. Our analysis reveals both universal and language-specific patterns in handshape usage, movement dynamics, non-manual features, and spatial articulation. We explore intra and inter-language similarity distributions, phonological clustering, and co-occurrence structures across feature types. The findings offer insights into the structural organization of sign language phonology and highlight typological variation shaped by linguistic and cultural factors.

🌉 Interdisciplinary Bridge — Machine Learning and Natural Language Processing
🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Speech & Audio