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Biometric-enabled Personalized Augmentative and Alternative Communications

About

This study focuses on the roadmapping of biometric technologies onto personalized Augmentative and Alternative Communication (AAC), a branch of assistive technologies for people with communication disabilities. This technology roadmapping revolves around the proposed notions of an AAC biometric register and biometric-enabled reconfigurable AAC channels. The biometric register is referred to as a tool for acquiring and processing physiological and behavioural traits that are essential for augmentative and alternative communication. It links biometric traits, such as gestures, to intermediate traits, such as synthesized speech, for customizable communication channels. The proposed methodology is used to assess the gaps between the social and practical demands, such as assisting people with communication disabilities in the contemporary semi-automated border control, and the emerging advances in AI, such as advanced video and speech processing. We provide two case studies of the AAC that rely on hand gesture recognition and sign language word recognition, and conclude that the current accuracy of those AI technologies does not meet the practical requirements. The proposed roadmapping provides recommendations for further improvement to close these gaps.

S. Yanushkevich, E. Berepiki, P. Ciunkiewicz, V. Shmerko, G. Wolbring, R. Guest• 2026

Related benchmarks

TaskDatasetResultRank
Sign Language RecognitionSLR500--
19
Word-level sign language recognitionWLASL 300--
11
Word-level sign language recognitionWLASL 2000
Top-1 Acc69
8
Gesture RecognitionDHG-14/28--
6
Sign Language RecognitionWLASL100--
5
Sign Language RecognitionWLASL 1000--
3
Gesture RecognitionStatic HAnd PosE (SHAPE) Dataset--
1
Gesture RecognitionNTU-RGBD--
1
Gesture RecognitionKinetics-Skeleton--
1
Sign Language RecognitionASLLVD Dataset--
1
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