arXiv:2609.18772v1 Announce Type: new
Abstract: Sign language processing advances rapidly for high-resource languages such as American Sign Language (ASL), yet most of the world's sign languages lack...
By Marcel Granero-Moya, Carolina del Corral Farrar\'os, Gloria Haro, Coloma Ballester, Ricardo Marques
The paper introduces FS23K, a large-scale British Sign Language fingerspelling dataset created through an iterative annotation framework. It also presents a recognition model that incorporates bi‑manual interactions and mouthing cues, achieving a halved character error rate compared to previous state‑of‑the‑art methods. These results underscore the dataset’s and model’s value for advancing sign language research and automated annotation pipelines.
By Alyssa Chan, Taein Kwon, Andrew Zisserman
SignSeek is a new method for learning transferable sign representations that enables efficient retrieval of signs from dictionaries using only a query video. It employs contrastive learning with saliency‑guided articulator masking, aligning same‑gloss signs across signers while focusing on the single most critical articulator per sign. Trained on 266K samples from multiple sign languages, SignSeek achieves state‑of‑the‑art cross‑corpus retrieval performance and zero‑shot generalisation to unseen British Sign Language, also improving isolated sign recognition and subtitle alignment.
By Sobhan Asasi, Ozge Mercanoglu Sincan, Richard Bowden
arXiv:2609.25862v1 Announce Type: new
Abstract: We present the first experiments on isolated sign language recognition (ISLR) for Icelandic Sign Language (\'ITM). We use \'ITM SignWiki, a dataset der...
By Finnur \'Ag\'ust Ingimundarson, Gu{\dh}n\'y Bj\"ork {\TH}orvaldsd\'ottir, Mathias M\"uller, Sarah Ebling
SignBind-LLM introduces a modular framework for sign language translation that separates continuous signing, fingerspelling, and lipreading into dedicated expert streams. Each expert is pre‑trained independently on about two million pseudo‑gloss sequences, eliminating the need for manual gloss annotation. A lightweight transformer fuses the expert outputs, and a pre‑trained language model converts the fused pseudo‑glosses into fluent English, achieving state‑of‑the‑art performance on multiple benchmarks with lower training cost.
By Marshall Thomas, Edward Fish, Richard Bowden
arXiv:2606. 19352v1 Announce Type: cross Abstract: Sign languages are expressive visual languages used by Deaf and Hard-of-Hearing (DHH) communities.
By Yiming Ni, Zhi-Qi Cheng, Jiayu Li, Wei Cheng