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Translation System for Sign Language Learning

Author

Listed:
  • Jibin Joy
  • N Meenakshi
  • Thejas Vinodh
  • Abel Thomas
  • Shifil S

Abstract

Sign language display software converts text/speech to animated sign language to support the special needs population, aiming to enhance communication comfort, health, and productivity. Advancements in technology, particularly computer systems, enable the development of innovative solutions to address the unique needs of individuals with special requirements, potentially enhancing their mental well-being. Using Python and NLP, a process has been devised to detect text and live speech, converting it into animated sign language in real-time. Blender is utilized for animation and video processing, while datasets and NLP are employed to train and convert text to animation. This project aims to cater to a diverse range of users across different countries where various sign languages are prevalent. By bridging the gap between linguistic and cultural differences, such software not only facilitates communication but also serves as an educational tool. Overall, it offers a cost-effective and widely applicable solution to promote inclusivity and accessibility.

Suggested Citation

  • Jibin Joy & N Meenakshi & Thejas Vinodh & Abel Thomas & Shifil S, 2024. "Translation System for Sign Language Learning," International Journal of Scientific Research in Computer Science, Engineering and Information Technology, International Journal of Scientific Research in Computer Science, Engineering and Information Technology, vol. 10(2), pages 487-493, April.
    • Handle: RePEc:jbh:ijsrcs:v10:y2024:i2:id:71
    DOI: 10.32628/CSEIT2410257
    Note: Article URL: https://ijsrcseit.com/home/article/view/CSEIT2410257
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