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Sign Language Detection and Translator with Learning Platform Usability

Asmi Mishra, Vikash Chaudhary, Udit Bhardwaj

2026ensign languagegesture recognitionassistive technologydeep learningreal-time translationaccessibility

Abstract

Language:

Even though assistive technologies have advanced, deaf and hard-of-hearing people in India still face major communication barriers due to limited awareness and resources. This work proposes a real-time, browser-based sign language recognition and multilingual translation system that operates entirely on client-side, commodity hardware. Using MediaPipe, the system efficiently extracts hand landmarks, which are then processed by a Convolutional Neural Network (CNN) to recognize sign gestures. Recognized signs are translated into multiple languages, including Indian regional languages such as Hindi, Marathi, Bengali, Tamil, and Punjabi, via external translation APIs with priority given to DeepL. The platform also provides a learning-oriented dashboard that tracks users’ practice frequency, interaction history, and progress, supporting both American Sign Language (ASL) and Indian Sign Language (ISL). Experimental results indicate moderate accuracy with low latency, demonstrating that real-time sign language recognition and translation is feasible on standard web platforms without specialized equipment.

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Cite This Work

@article{862b3c7e-13e8-475e-9a6c-2947ce989204,
  title={Sign Language Detection and Translator with Learning Platform Usability},
  author={Asmi Mishra and Vikash Chaudhary and Udit Bhardwaj},
  year={2026},
  language={en}
}
TY  - JOUR
TI  - Sign Language Detection and Translator with Learning Platform Usability
AU  - Asmi Mishra
AU  - Vikash Chaudhary
AU  - Udit Bhardwaj
PY  - 2026
LA  - en
ER  -

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