AI- enabled real-time speech -to- sign language conversion with an interactive chatbot and a learning module.

Author(s)	Ms. SATHVIKA A, Ms. HEMALATHA J, Prof. CHINCHU NAIR, Dr. R.SHOBA RANI RANI, Dr. JERALD F
Country	India
Abstract	This project presents an innovative Sign Language Chatbot system designed to bridge communication gaps for the deaf and hard-of-hearing community. The system takes real-time sign language inputs, recognizes them using a Ridge Classifier-based model, and generates meaningful responses through an NLP and CNN-powered chatbot engine. Additionally, the chatbot produces a dynamic sign language avatar, visually delivering responses in sign form. To further support learning, the platform includes a training module where users can input text or voice commands and receives corresponding sign language outputs, enabling interactive and accessible sign language education. By integrating machine learning, computer vision, and natural language processing, this project creates a two-way communication and learning environment, promoting inclusivity and sign language literacy.
Keywords	SIGN LANGUAGE RECOGNITION, MACHINE LEARNING, CONVOLUTIONAL NEURAL NETWORKS (CNN), HAND GESTURE RECOGNITION, OPENCV, RIDGE CLASSIFIER.
Field	Computer Applications
Published In	Volume 8, Issue 2, March-April 2026
Published On	2026-03-16

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