NATURAL SENTENCE GENERATION USING SIGN LANGUAGE GESTURES

NATURAL SENTENCE GENERATION USING SIGN LANGUAGE GESTURES

Mrs. Ancy Y Das , Assistant Professor, Computer Science and Engineering  at BGS Institute  of Technology, Adichunchanagiri University , ancyydas@bgsit.ac.in ,

BG Nagara , Karnataka

Sushmitha C S, 4th Year, 8th Sem  Department of Computer Science and Engineering at BGS Institute of Technology, Adichunchanagiri University cssushmitha38@gmail.com ,

BG Nagara, Karnataka

Abstract: The utilize of sign dialect essentially improves communication for people with hearing disabilities, serving as the essential mode of communication for those who don't utilize verbal dialect. American Sign Dialect (ASL) is famous for its adequacy in encouraging communication among the hearing-impaired. This inventive arrangement leverages innovation to bridge the communication boundary between non-signers and people with hearing disabilities, advancing inclusivity and shared understanding. The proposed venture utilizes progressed innovation to identify ASL signals and interpret them into coherent English sentences, in this manner empowering consistent communication between underwriters and non-signers. By joining MobileNetV2 for sign dialect signal acknowledgment and utilizing Common Dialect Handling (NLP) strategies for sentence era, this activity not as it were distinguishes visual expressions in ASL but too changes them into important English sentences.This combination of computer vision and dialect handling advances holds colossal guarantee in upgrading communication openings for people who are hard of hearing or difficult of hearing, enabling them to lock in more viably with the more extensive community.

Keywords: WLASL, NLP, MobileNetV2, Profound Learning, CNN, T5, TKinter, Sign Dialect.