This paper introduces the Gray Wolf Optimized Convolutional Transformer Network, a combined deep learning framework aimed at accurately and efficiently recognizing dynamic hand gestures, especially in American Sign Language (ASL). The model integrate...
Sign language recognition is crucial in bridging the communication gaps between hearing and deaf communities. In this study, we build on an existing sign language classification model based on the VGG19 architecture, enhancing its robustness through ...
Generally, the interaction of gestures presents a set of benefits to persons with disabilities, from improving motor, social, and cognitive skills to delivering a secure and controlled atmosphere for engaging in real-world scenarios. Automatic detect...
Saudi Arabic Sign Language (SArSL) recognition poses significant challenges due to its complex spatio-temporal structure and the scarcity of annotated datasets. This paper introduces a self-supervised learning framework built upon the Video Momentum ...
This study proposes an environment- and signer-invariant sign language recognition model. The model first extracts skeletal key-points from the signer via MediaPipe, which is Google's cross-platform pipeline framework that helps to detect and track h...
This paper presents a vision transformer-based, context-aware, real-time Indian Sign Language (ISL) conversational agent designed to enhance digital accessibility for India's Deaf and Hard-of-Hearing community within e-governance services. The system...
Communication between deaf or mute individuals and hearing persons is often hindered by the lack of mutual understanding of sign or vocal language. To bridge this gap, Indian Sign Language Recognition (ISLR) systems are essential. This paper proposes...
Sign language (SL) is a significant communication method for individuals with hearing impairments, using hand gestures to convey letters, words, and sentences. However, several people are unfamiliar with SL, creating a communication gap. An intellige...
Sign language (SL) is a non-verbal language applied by deaf and hard-of-hearing individuals for daily communication between them. Studies in SL recognition (SLR) have recently become essential developments. The current successes present the base for ...
Sign language recognition (SLR) has the potential to bridge communication gaps and empower hearing-impaired communities. To ensure the portability and accessibility of the SLR system, its implementation on a portable, server-independent device become...
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