A strong vision-based pipeline that combines temporal modeling and keypoint-based feature extraction for categorizing solitary Indian Sign Language adjective gestures and introduces efficient keypoint-based augmentation and evaluates multiple Recurrent Neural Network variants for fine-grained adjective recognition is shown.
A sign language recognition system based on deep learning and computer vision that translates hand gestures into textual output through real-time image and video processing to support communication between deaf and hard-of-hearing individuals and the community is presented.
Milia Habib, Teddy Nohra, Charbel Srour et al.· Advances in Artificial Intel...· 0 citations
Communication barriers between deaf and hard-ofhearing (DHH) individuals and the hearing population remain a pressing global challenge, compounded in India by a severe shortage of certified Indian Sign Language (ISL) interpreters. This paper presents SignAssistant, a real-time, AI-enabled gesture-tospeech system that t...
Indian Sign Language (ISL) is the first language for millions of deaf and mute people in India. However, the development of efficient, real, time automatic ISL interpretation systems has been hindered by numerous challenges such as signer variability, scarcity of large annotated datasets, complicated hand articulations...
Chirag Prajapati, Atul M. Gonsai· International journal of com...· 0 citations
This paper presents a comprehensive review of existing datasets, methodologies, and experimental frameworks for Indian Sign Language (ISL) recognition and translation, highlighting recent advancements driven by deep learning architectures such as Convolutional Neural Networks (CNNs), Long Short-Term Memory (LSTM) netwo...
Shefali Khera, Shreya, Meghna Sharma et al.· International Journal on Com...· 0 citations
SignAura is introduced, an artificial intelligence-driven real-time SLSL sign-recognition system that provides multilingual lexical text and synthesized speech and performs isolated sign-level recognition and provides corresponding multilingual lexical output rather than complete grammatical sign-language translation.
Pramudhi Hansi Wijesinghe, Nimesh Pollwaththage, D. Dhammearatchi· Journal of Innovation in Sci...· 0 citations
This proposed research presents a real-time American Sign Language (ASL) recognition system for 24 dynamic signs that integrates the MediaPipe frame work with Long Short-Term Memory (LSTM) network to achieve efficient real-time dynamic sign recognition with reduced computational and data requirements.
Youssef Farhan, Zineb Haimer, Oumaima Lamaamar et al.· 0 citations
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