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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:10.55041/IJSREM28223

Sign Language Analysis Using CNN Algorithm

Stream/Area:

-

Subject:

-

Paper ID:

10.55041/IJSREM28223

Volume:

8 |

1 |

Jan 2024

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM28223

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

P

Prof.S.P.Gunjal

MAG

Mansi Ajay Ghorpade

YMK

Yashada Mahesh Kardekar

KJP

Komal Jagat Patil

KGB

Kunal Gorakh Borude

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Abstract

Sign language is a rich and diverse mode of communication used by Deaf and hard of-hearing communities around the world. This paper presents a comprehensive analysis of sign language, focusing on its linguistic and gestural elements. Our study encompasses an exploration of the structural properties of sign languages, their historical evolution, and the cognitive and neural mechanisms underlying sign language processing. We begin by providing an overview of sign language as a natural and fully developed language with its own syntax, semantics, and phonological features. Drawing from various sign languages, including American Sign Language (ASL), British Sign Language (BSL), and others, we investigate the grammatical aspects and iconicity within signs. Furthermore, we examine the role of facial expressions and non-manual markers in conveying essential linguistic information. This analysis also delves into the historical and cultural dimensions of sign languages, shedding light on the evolution of sign languages and the influence of Deaf culture on their development. It highlights the importance of recognizing sign languages as unique cultural and linguistic entities, distinct from spoken languages.

KEYWORDS

Computer Vision Convolutional Neural Networks Sign Language Recognition

Cite This Article

Prof.S.P.Gunjal, Mansi Ajay Ghorpade, Yashada Mahesh Kardekar, Komal Jagat Patil, Kunal Gorakh Borude, "Sign Language Analysis Using CNN Algorithm," International Journal of Scientific Research in Engineering and Management, vol. 8, no. 1, Jan 2024. https://doi.org/10.55041/IJSREM28223

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Publication Date

12/31/45311

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Double-Blind Peer Review

Review Rounds: 2

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The authors declare no conflict of interest related to this research work.

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