Recognising and Converting Sign Language into Speech

Registration ID: IJNRD_201283

Published ID: IJNRD2307387

DOI: Click Here to Get

Vaishnavi Athrey , Dr.Deepashree Devaraj

Machine Learning models, OTSU Methods, Vision-based approach, Convolutional Neural Networks, ReLu, Softmax

This paper presents a comprehensive study on recognizing and converting sign language to speech using machine learning models based on Convolutional Neural Networks (CNNs) with a vision-based approach and the OTSU method. Sign language is a vital means of communication for the deaf community, and bridging the communication gap between the deaf and hearing communities is crucial for inclusivity and accessibility. We propose an innovative approach that combines the power of CNNs, a vision-based approach, and the OTSU method for robust and accurate sign language recognition and translation into spoken language.

Published Paper   E-Certificate

Vaishnavi Athrey & Dr.Deepashree Devaraj (July-2023). Recognising and Converting Sign Language into Speech. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 8(7), d759-d767. https://ijnrd.org/papers/IJNRD2307387.pdf

Volume 8 Issue 7, July-2023

Pages : d759-d767

Paper Reg. ID: IJNRD_201283

Published Paper Id: IJNRD2307387

Downloads: 000121977

Research Area: Engineering

Country: Bengaluru, Karnataka, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2307387.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2307387

Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

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