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This chapter aims to bridge communication gaps for the hearing and speech-impaired community by leveraging artificial intelligence to recognize sign language gestures in real time and translate them into text and speech. This innovative platform integrates advanced machine learning models for accurate gesture detection and real-time translation, all through a user-friendly interface designed for inclusivity and ease of use. Prioritizing scalability and reliability, SIGN BRIDGE is adaptable to various settings, including healthcare, education, and public services, even in resource-constrained environments. By empowering individuals with hearing and speech impairments, the chapter fosters independence, inclusivity, and equitable access to essential services, paving the way for a more connected and inclusive society.

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AI-Integrated Real-Time Sign Language Recognition: SIGN BRIDGE

  • 会议论文

  • 发表日期：

    2026年

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  • Lingala Thirupathi,
  • Ch. Vijaya Bhaskar,
  • Dheeraj Sundaragiri,
  • Shyam Sunder Pabboju,
  • Balne Sai Vignesh

摘要

This chapter aims to bridge communication gaps for the hearing and speech-impaired community by leveraging artificial intelligence to recognize sign language gestures in real time and translate them into text and speech. This innovative platform integrates advanced machine learning models for accurate gesture detection and real-time translation, all through a user-friendly interface designed for inclusivity and ease of use. Prioritizing scalability and reliability, SIGN BRIDGE is adaptable to various settings, including healthcare, education, and public services, even in resource-constrained environments. By empowering individuals with hearing and speech impairments, the chapter fosters independence, inclusivity, and equitable access to essential services, paving the way for a more connected and inclusive society.