Journal of Intelligent Communication

Article

Developing an Intelligent Recognition System for British Sign Language: A Step Towards Inclusive Communication

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https://doi.org/10.54963/jic.v4i1.351
Isiaq, S. O., & Stephen, S. (2025). Developing an Intelligent Recognition System for British Sign Language: A Step Towards Inclusive Communication. Journal of Intelligent Communication, 4(1), 42–57. https://doi.org/10.54963/jic.v4i1.351
Volume 4 Issue 1 (2025): In Progress
Copyright (c) 2025 Sakirulai Olufemi Isiaq, Shany Stephen
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Authors

  • Sakirulai Olufemi Isiaq

    Creative Computing Institute, University of Arts London, London WC1V 7EY, UK
  • Shany Stephen

    Department of Computing, Solent University, Southampton SO14 0YN, UK

Effective communication is crucial for ensuring inclusivity, yet the hard-of-hearing community faces significant barriers due to a shortage of qualified interpreters. British Sign Language (BSL), officially recognised in the UK, relies on hand gestures, facial expressions, and body movements. However, limited interpreter availability necessitates technological solutions to bridge the communication gap between signers and non-signers. This study proposes a real-time, vision-based BSL recognition system using computer vision and deep learning to interpret fingerspelling and six commonly used BSL words. The system employs OpenCV for video capture, MediaPipe for hand feature extraction, and Long Short-Term Memory (LSTM) networks for sign classification. A dataset incorporating left- and right-handed signers achieved a 94.23% accuracy rate for 26 fingerspelling gestures and 99.07% for six words. To enhance usability, a graphical user interface was developed, enabling seamless real-time interaction. These findings demonstrate the potential of AI-driven sign language recognition to improve accessibility and foster more inclusive communication for the hard-of-hearing community.

Keywords:

British Sign Language; Realtime Recognition; Media Pipe; Hard‑of‑Hearing; LSTM; OpenCV

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