Real Time Sign Language Recognition and Speech Generation

Author:

Thakur Amrita,Budhathoki Pujan,Upreti Sarmila,Shrestha Shirish,Shakya Subarna

Abstract

Sign Language is the method of communication of deaf and dumb people all over the world. However, it has always been a difficulty in communication between a verbal impaired person and a normal person. Sign Language Recognition is a breakthrough for helping deaf-mute people to communicate with others. The commercialization of an economical and accurate recognition system is today’s concern of researchers all over the world. Thus, sign language recognition systems based on Image processing and neural networks are preferred over gadget system as they are more accurate and easier to make. The aim of this paper is to build a user friendly and accurate sign language recognition system trained by neural network thereby generating text and speech of the input gesture. This paper also presents text to sign language generation model that enables a way to establish a two-way communication without the need of a translator.

Publisher

Inventive Research Organization

Cited by 31 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. A machine learning-driven web application for sign language learning;Frontiers in Artificial Intelligence;2024-06-18

2. Identification of Emotions in a Given Speech Audio Clip by Using ANN;2024 International Conference on Emerging Technologies in Computer Science for Interdisciplinary Applications (ICETCS);2024-04-22

3. An improved custom convolutional neural network based hand sign recognition using machine learning algorithm;Engineering Reports;2024-03-19

4. Real-time speech to sign language converter in GIF format;AIP Conference Proceedings;2024

5. Hand Sign Detection and Voice Conversion for the Hearing and Speech Impaired Using Convolutional Neural Networks;Lecture Notes in Networks and Systems;2024

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