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International Journal of Research and Innovation in Applied Science (IJRIAS)

Signconnect: Real-Time Communication Bridge for the Specially-Abled

byShubham; Nancy

Published April 18, 2026  •  Vol. 11, Issue 3, pp. 1397–1406Open Access
DOI: 10.51584/IJRIAS.2026.11030107

Abstract

Communication gap between the deaf and hearing communities remains an important obstacle to social integration. Recent advances in artificial intelligence, in particular, in the fields of deep learning and computer vision, have also provided the prospect of truly radical assistive technologies that could translate sign language gestures to readable text or spoken audio in real time. The current study introduces a novel system of real-time sign language interpretation, which integrates the multi-modal gesture recognition, flexible deep neural networks, and context-based translation schemes to support effective and natural user interactions. The system that was developed uses the convolutional and recurrent neural network architectures to process the spatial and temporal properties of signing gestures. A dedicated set of movements of the Indian Sign language (ISL) was created based on MediaPipe Holistic and OpenCV to obtain the hand, face, and body keypoints and to be trained comprehensively with the help of the TensorFlow workflows. The model is optimized to the minimal-latency processing which ensures fluid real-time interpretation on devices with limited processing power. Besides making progress in the technical aspects of instantaneous gesture recognition, this research will provide a solution to an im- portant social need; that of allowing people with new auditory or speech disabilities to communicate easily and independently. The system has a high recognition accuracy, adaptability to different illumination and environmental conditions, and sequential sign pattern expansion. Also, the architecture offers a platform upon which new features, including gesture- to-voice translation, cross- linguistic understanding, and portability or mobile compatibility will be built. By integrating technology enhancement with the human-centered design concepts, this study provides a scaling, efficient, and holistic solution that enhances the level of access and facilitates the equity of communication across all the societal groups.

Keywords: Real-Time Translation, Sign Language Recognition

JournalInternational Journal of Research and Innovation in Applied Science (IJRIAS)
ISSN2454-6194
Volume / IssueVolume 11, Issue 3
Pages1397–1406
Publication dateApril 18, 2026
DOI10.51584/IJRIAS.2026.11030107
PublisherRSIS International
LicenseOpen Access

How to cite this article

Shubham, & Nancy (2026). Signconnect: Real-Time Communication Bridge for the Specially-Abled. International Journal of Research and Innovation in Applied Science (IJRIAS), 11(3), 1397-1406. https://doi.org/10.51584/IJRIAS.2026.11030107

BibTeX

@article{Shubham2026,
  title   = {Signconnect: Real-Time Communication Bridge for the Specially-Abled},
  author  = {Shubham and Nancy},
  journal = {International Journal of Research and Innovation in Applied Science (IJRIAS)},
  volume  = {11},
  number  = {3},
  pages   = {1397--1406},
  year    = {2026},
  doi     = {10.51584/IJRIAS.2026.11030107},
  publisher = {RSIS International}
}