Publication Type : Conference Paper
Publisher : 8th IEEE International Conference on Computational Intelligence and Computing Research, ICCIC 2017
Source : 8th IEEE International Conference on Computational Intelligence and Computing Research, ICCIC 2017, Tamilnadu College of Engineering, India,, 2017.
Campus : Bengaluru
School : School of Engineering
Center : Electronics Communication and Instrumentation Forum (ECIF)
Department : Electronics and Communication
Year : 2017
Abstract : Human beings interact with each other to convey their ideas, thoughts, and experiences to the people around them. But this is not the case for deaf-mute people. Sign language paves the way for deaf-mute people to communicate. Through sign language, communication is possible for a deaf-mute person without the means of acoustic sounds. The aim behind this work is to develop a system for recognizing the sign language, which provides communication between people with speech impairment and normal people, thereby reducing the communication gap between them. Compared to other gestures (arm, face, head and body), hand gesture plays an important role, as it expresses the user's views in less time. In the current work flex sensor-based gesture recognition module is developed to recognize English alphabets and few words and a Text-to-Speech synthesizer based on HMM is built to convert the corresponding text.
Cite this Research Publication : V. D, Aishwarya, H. M., K, N., T, R. B., and Dr. T. K. Ramesh, “Sign language to speech conversion”, in 8th IEEE International Conference on Computational Intelligence and Computing Research, ICCIC 2017, Tamilnadu College of Engineering, India,, 2017.