• Prajwal Ratnakant Berad
• Yogesh Gajanan Pawar
• Mohini Sanjay Gawade
• Hari Vijay Shelar
• Dr.Deepali S Hirolikar

This topic is all about developing a successful Sign language recognition and translation system which is helpful for people with certain disabilities who can’t use present voice enabled Virtual Assistants. Communication is important with people as it helps us understand them and gain knowledge. In case of Deaf & mute people, this becomes a problem. It is solved by creating a virtual assistant built to recognize hand gestures and translate them in normal language to perform tasks ordered by the user. This certainly helps other normal people to successfully communicate with deaf & mute people Without worrying about any misunderstanding at the listener’s end. There are more than 300 sign languages used by various cultural groups worldwide. In this article, we provide a technique for generating a sign language dataset using a camera, followed by the training of a TensorFlow model using transfer learning to produce a real-time sign language recognition system. Despite the small amount of the dataset, the system still performs well.

Deep Learning, Virtual Assistants, Tensor Flow, Convolutional Neural Network Hand Gestures, Sign Languages

"Virtual Personal Assistant With Sign Language", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 5, page no.c571-c573, May-2023, Available :http://www.jetir.org/papers/JETIR2305283.pdf

"Virtual Personal Assistant With Sign Language", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 5, page no. ppc571-c573, May-2023, Available at : http://www.jetir.org/papers/JETIR2305283.pdf