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Title: :  A Survey of Machine Learning Techniques for Sign Language Translation
PaperId: :  22722
Published in:   International Journal Of Advance Research And Innovative Ideas In Education
Publisher:   IJARIIE
e-ISSN:   2395-4396
Volume/Issue:    Volume 10 Issue 2 2024
DUI:    16.0415/IJARIIE-22722
Licence: :   IJARIIE is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Author NameAuthor Institute
Manish KumarDayananda Sagar Academy of Technology and Management (DSATM)
Ayush KumarDayananda Sagar Academy of Technology and Management (DSATM)
Aditi PatniDayananda Sagar Academy of Technology and Management (DSATM)
Gourav MishraDayananda Sagar Academy of Technology and Management (DSATM)
Sridevi G M Dayananda Sagar Academy of Technology and Management (DSATM)

Abstract

Computer Engineering
Sign language recognition, Machine learning algorithms, Convolutional Neural Network (CNN), K-Nearest Neighbor (KNN), Random Forest, Support Vector Machine (SVM), American Sign Language (ASL), Accessibility, Communication, Inclusivity, Training tool, Real-time recognition, Gesture recognition, Image processing, Computer vision, Keypoint detection, Accuracy, Social inclusion, Semantic understanding.
Bridging the communication gap between deaf and non-verbal communities has long been a vital objective, with sign language recognition playing a crucial role. This research delves into the realm of automated sign language recognition, specifically focusing on American Sign Language (ASL) and leveraging the prominent ASL pickle data. Employing various machine learning algorithms, including Random Forest, Support Vector Machines, Convolutional Neural Network and K Nearest Neighbors, this study investigates key-point detection-based approaches to ASL recognition. The model's performance is analyzed in great detail through exhaustive testing, utilizing metrics such as F1 score, precision, and recall to determine the most effective approach. To improve user interaction, a user friendly graphical user interface (GUI) is implemented, allowing for effortless interaction and prediction generation using the best machine learning model. Additionally, this paper provides a thorough review of the various techniques used for sign language translation.

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IJARIIE Manish Kumar, Ayush Kumar, Aditi Patni, Gourav Mishra, and Sridevi G M . "A Survey of Machine Learning Techniques for Sign Language Translation" International Journal Of Advance Research And Innovative Ideas In Education Volume 10 Issue 2 2024 Page 191-200
MLA Manish Kumar, Ayush Kumar, Aditi Patni, Gourav Mishra, and Sridevi G M . "A Survey of Machine Learning Techniques for Sign Language Translation." International Journal Of Advance Research And Innovative Ideas In Education 10.2(2024) : 191-200.
APA Manish Kumar, Ayush Kumar, Aditi Patni, Gourav Mishra, & Sridevi G M . (2024). A Survey of Machine Learning Techniques for Sign Language Translation. International Journal Of Advance Research And Innovative Ideas In Education, 10(2), 191-200.
Chicago Manish Kumar, Ayush Kumar, Aditi Patni, Gourav Mishra, and Sridevi G M . "A Survey of Machine Learning Techniques for Sign Language Translation." International Journal Of Advance Research And Innovative Ideas In Education 10, no. 2 (2024) : 191-200.
Oxford Manish Kumar, Ayush Kumar, Aditi Patni, Gourav Mishra, and Sridevi G M . 'A Survey of Machine Learning Techniques for Sign Language Translation', International Journal Of Advance Research And Innovative Ideas In Education, vol. 10, no. 2, 2024, p. 191-200. Available from IJARIIE, https://ijariie.com/AdminUploadPdf/A_Survey_of_Machine_Learning_Techniques_for_Sign__Language_Translation_ijariie22722.pdf (Accessed : 07 March 2024).
Harvard Manish Kumar, Ayush Kumar, Aditi Patni, Gourav Mishra, and Sridevi G M . (2024) 'A Survey of Machine Learning Techniques for Sign Language Translation', International Journal Of Advance Research And Innovative Ideas In Education, 10(2), pp. 191-200IJARIIE [Online]. Available at: https://ijariie.com/AdminUploadPdf/A_Survey_of_Machine_Learning_Techniques_for_Sign__Language_Translation_ijariie22722.pdf (Accessed : 07 March 2024)
IEEE Manish Kumar, Ayush Kumar, Aditi Patni, Gourav Mishra, and Sridevi G M , "A Survey of Machine Learning Techniques for Sign Language Translation," International Journal Of Advance Research And Innovative Ideas In Education, vol. 10, no. 2, pp. 191-200, Mar-App 2024. [Online]. Available: https://ijariie.com/AdminUploadPdf/A_Survey_of_Machine_Learning_Techniques_for_Sign__Language_Translation_ijariie22722.pdf [Accessed : 07 March 2024].
Turabian Manish Kumar, Ayush Kumar, Aditi Patni, Gourav Mishra, and Sridevi G M . "A Survey of Machine Learning Techniques for Sign Language Translation." International Journal Of Advance Research And Innovative Ideas In Education [Online]. volume 10 number 2 (07 March 2024).
Vancouver Manish Kumar, Ayush Kumar, Aditi Patni, Gourav Mishra, and Sridevi G M . A Survey of Machine Learning Techniques for Sign Language Translation. International Journal Of Advance Research And Innovative Ideas In Education [Internet]. 2024 [Cited : 07 March 2024]; 10(2) : 191-200. Available from: https://ijariie.com/AdminUploadPdf/A_Survey_of_Machine_Learning_Techniques_for_Sign__Language_Translation_ijariie22722.pdf
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