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Vision transformer-powered conversational agent for real-time Indian Sign Language e-governance accessibility.

Prema Nedungadi1, Gautham Dileep2, M Geetha3

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Summary
This summary is machine-generated.

This study introduces a real-time Indian Sign Language (ISL) agent for e-governance, improving digital access for the Deaf and Hard-of-Hearing community. The system achieves high accuracy and fast responses, enabling inclusive digital interactions.

Keywords:
Artificial intelligenceAssistive technologyAugmentative and alternative communicationChatbotDigital IndiaGesture recognitionVideo recognition

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Area of Science:

  • Computer Science
  • Artificial Intelligence
  • Human-Computer Interaction

Background:

  • The Deaf and Hard-of-Hearing community faces significant digital accessibility barriers, particularly in accessing e-governance services.
  • Indian Sign Language (ISL) is a low-resource language, posing challenges for developing effective digital tools.
  • Existing systems often lack the context-awareness and real-time processing needed for natural conversational interactions.

Purpose of the Study:

  • To develop a context-aware, real-time Indian Sign Language (ISL) conversational agent.
  • To enhance digital accessibility for the Deaf and Hard-of-Hearing community in e-governance.
  • To support continuous ISL recognition from isolated words to full sentences.

Main Methods:

  • Utilized a hybrid architecture combining Convolutional Neural Networks (CNNs) with Vision Transformer (ViT) models.
  • Developed a domain-specific ISL video dataset to address low-resource challenges.
  • Implemented a dynamic context-response mapping engine for improved accuracy with ambiguous inputs.

Main Results:

  • Achieved 97.5% accuracy under optimized conditions.
  • Demonstrated a mean response time of 6.53 seconds.
  • Attained an average System Usability Scale (SUS) score of 71.83.

Conclusions:

  • The developed ISL conversational agent significantly enhances digital inclusion for the Deaf and Hard-of-Hearing community.
  • The system's modular design and context-aware engine ensure scalability and reliability for real-world deployment.
  • This advancement facilitates real-time, inclusive digital interactions within e-governance services.