Volume no :
10 |
Issue no :
1
Article Type :
Google Scholar
Author :
Mrs. Abinaya N, Kalaivani. C, Kenish.K, Mohamed Noorul Irfan.M, Pragin Barath.M
Published Date :
21 - March - 2026
Publisher :
Journal of Artificial Intelligence and Cyber Security (JAICS)
Page No: 1 - 7
Abstract : Communication barriers faced by individuals with hearing impairments significantly impact their daily interactions. This paper presents a Speech-to-Sign Translation and Accessibility System that leverages Artificial Intelligence (AI) and Natural Language Processing (NLP) to convert spoken language into real-time sign language. The system uses speech recognition algorithms to capture and process spoken words, which are then translated into sign language gestures and displayed through an animated avatar. By integrating machine learning models with a gesture synthesis engine, it ensures accurate and context-aware translations. Additionally, the system provides a user-friendly interface to enhance accessibility, aiming to bridge communication gaps, promote inclusivity, and enable seamless interaction for the deaf and hard-of-hearing community in both public and private environments.
Keyword Speech-to-sign translation, ASR, NLP, 3D avatar, sign language synthesis
Reference:

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