Manuscript Number : IJSRST206311

Sign Language Recognition using Convolutional Neural Network

Authors(3) :-Prof. Pradyumna P. Kulkarni, Suraj S. Bhute, Akash P. Wagh

The inability to speak is considered to be a true disability. People with this disability use different modes to communicate with others, the hand gesture is one of the methods used in sign language for non-verbal communication. Developing sign language application for deaf people are often vital, as they

Authors and Affiliations

Prof. Pradyumna P. Kulkarni
Computer Science and Engineering, Anuradha Engineering College, Sant Gadgebaba Amravati, Chikhli, India
Suraj S. Bhute
Computer Science and Engineering, Anuradha Engineering College, Sant Gadgebaba Amravati, Chikhli, India
Akash P. Wagh
Computer Science and Engineering, Anuradha Engineering College, Sant Gadgebaba Amravati, Chikhli, India

Sign Language Recognition, Convolutional Neural Network, Recurrent Neural Network, ISL

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  3. J Singha, K DasIndian “Sign Language Recognition Using Eigen Value Weighted Euclidean Distance Based Classification Technique.” arXiv preprint arXiv:1303.0634, 4 (2) (2013), pp. 188-195
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  8. Rakesh.B.S, Tamilarasan.S, Avinash N, “Hand Gesture Recognition based on Real-time Indian Sign Language,” International Journal of Computer Sciences and Engineering, Vol.7, Issue.7, pp.181-185, 2019.
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  19. J. Atwood, M. Eicholtz, and J. Farrell. American Sign Language Recognition System. Artificial Intelligence and Machine Learning for Engineering Design. Dept. of Mechanical Engineering, Carnegie Mellon University, 2012

Publication Details

Published in : Volume 5 | Issue 6 | January-February 2020
Date of Publication : 2020-02-17
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 48-58
Manuscript Number : IJSRST206311
Publisher : Technoscience Academy

Print ISSN : 2395-6011, Online ISSN : 2395-602X

Cite This Article :

Prof. Pradyumna P. Kulkarni, Suraj S. Bhute, Akash P. Wagh, " Sign Language Recognition using Convolutional Neural Network", International Journal of Scientific Research in Science and Technology(IJSRST), Print ISSN : 2395-6011, Online ISSN : 2395-602X, Volume 5, Issue 6, pp.48-58, January-February-2020.
Journal URL : https://ijsrst.com/IJSRST206311
Citation Detection and Elimination     |      | |
  • Aditi Kalsh, N.S Garewal, Sign Language Recognition System, International Journal of Computational Engineering Research, pp. 15-21, vol. 3.”.
  • J Singha, K DasIndian “Sign Language Recognition Using Eigen Value Weighted Euclidean Distance Based Classification Technique.” arXiv preprint arXiv:1303.0634, 4 (2) (2013), pp. 188-195
  • Copyright © William Vicars, Sign Language resources at LifePrint.com,http://lifeprint.com/asl101/topics/wallpaper1.htm Accessed Jan 26, 2020]
  • Kar, Aradhana and Pinaki Sankar Chatterjee. “A Video-based Approach for Translating Sign Language to Simple Sentence in English.” (2010).
  • A. S. Nikam and A. G. Ambekar, "Sign language recognition using image based hand gesture recognition techniques," 2016 Online International Conference on Green Engineering and Technologies (IC-GET), Coimbatore,2016,pp.1-5.doi: 10.1109/GET.2016.7916786
  • M P, Paulraj & Yaacob, Sazali & Zanar Azalan, Mohd Shuhanaz & Palaniappan, Rajkumar. (2010). A phoneme based sign language recognition system using skin color segmentation. 1 - 5. 10.1109/CSPA.2010.5545253.
  • Rakesh.B.S, Tamilarasan.S, Avinash N, “Hand Gesture Recognition based on Real-time Indian Sign Language,” International Journal of Computer Sciences and Engineering, Vol.7, Issue.7, pp.181-185, 2019.
  • Sanil Jain and K.V.Sameer Raja,“Indian Sign Language Character Recognition”,.Available:https://cse.iitk.ac. in/users/cs365/2015/_submissions/vinsam/report.pdf Accessed Jan 16, 2020].
  • Andrej Karpathy,”CS231n: Convolutional Neural NetworksforVisualRecognition.”,Available: http://cs231n.github.io/convolutionalnetworks/ Accessed Jan 31, 2020]
  • D. Anbarasan | R. Aravind | K. Alice "GRS – Gesture based Recognition System for Indian Sign Language Recognition System for Deaf and Dumb People" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470,Volume-2Issue-2Februar2018,
  • Sumit saha,”A Comprehensive Guide to Convolutional NeuralNetworktheELI5way.”,Available: https://towardsdatascience.com/a-comprehensive-guide-to-convolutional -neural-networks-the-eli5-way-3bd2b1164a53Accessed Jan 31, 2020]
  • "Review of Different Deep Learning Approaches for Image Classification", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 3, page no.378-384, March-2019
  • Aishwarya,” Introduction to Recurrent Neural Network”, Available: https://www.geeksforgeeks.org/introduction-to-recurrent-neural-network/Accessed Jan 31, 2020]
  • Long ??,” Recurrent Neural Network And Long-Short Term Memory”, Available: https://ai.hblab.vn/2019/04/recurrent-neural-network-and-long-short.htmlAccessed Jan 31, 2020]
  • Arunava,”ConvolutionalNeuralNetwork“,Available:https://towardsdatascience.com/convolutional-neural-network-17fb77e76c05 Accessed Jan 31, 2020]
  • Mitchell, Ross; Young, Travas; Bachleda, Bellamie; Karchmer, Michael (2006). "How Many People Use ASL in the United States?: Why Estimates Need Updating" (PDF). Sign Language Studies (Gallaudet University Press.) 6 (3). ISSN 0302-1475. Retrieved November 27, 2012.
  • Y. Jia. Caffe: An open source convolutional architecture for fast feature embedding. http://caffe.berkeleyvision.org/, 2014.Lifeprint.com. American Sign Language (ASL) Manual Alphabet (fingerspelling) 2007
  • J. Atwood, M. Eicholtz, and J. Farrell. American Sign Language Recognition System. Artificial Intelligence and Machine Learning for Engineering Design. Dept. of Mechanical Engineering, Carnegie Mellon University, 2012
    • " target="_blank"> BibTeX     |
  • Aditi Kalsh, N.S Garewal, Sign Language Recognition System, International Journal of Computational Engineering Research, pp. 15-21, vol. 3.”.
  • J Singha, K DasIndian “Sign Language Recognition Using Eigen Value Weighted Euclidean Distance Based Classification Technique.” arXiv preprint arXiv:1303.0634, 4 (2) (2013), pp. 188-195
  • Copyright © William Vicars, Sign Language resources at LifePrint.com,http://lifeprint.com/asl101/topics/wallpaper1.htm Accessed Jan 26, 2020]
  • Kar, Aradhana and Pinaki Sankar Chatterjee. “A Video-based Approach for Translating Sign Language to Simple Sentence in English.” (2010).
  • A. S. Nikam and A. G. Ambekar, "Sign language recognition using image based hand gesture recognition techniques," 2016 Online International Conference on Green Engineering and Technologies (IC-GET), Coimbatore,2016,pp.1-5.doi: 10.1109/GET.2016.7916786
  • M P, Paulraj & Yaacob, Sazali & Zanar Azalan, Mohd Shuhanaz & Palaniappan, Rajkumar. (2010). A phoneme based sign language recognition system using skin color segmentation. 1 - 5. 10.1109/CSPA.2010.5545253.
  • Rakesh.B.S, Tamilarasan.S, Avinash N, “Hand Gesture Recognition based on Real-time Indian Sign Language,” International Journal of Computer Sciences and Engineering, Vol.7, Issue.7, pp.181-185, 2019.
  • Sanil Jain and K.V.Sameer Raja,“Indian Sign Language Character Recognition”,.Available:https://cse.iitk.ac. in/users/cs365/2015/_submissions/vinsam/report.pdf Accessed Jan 16, 2020].
  • Andrej Karpathy,”CS231n: Convolutional Neural NetworksforVisualRecognition.”,Available: http://cs231n.github.io/convolutionalnetworks/ Accessed Jan 31, 2020]
  • D. Anbarasan | R. Aravind | K. Alice "GRS – Gesture based Recognition System for Indian Sign Language Recognition System for Deaf and Dumb People" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470,Volume-2Issue-2Februar2018,
  • Sumit saha,”A Comprehensive Guide to Convolutional NeuralNetworktheELI5way.”,Available: https://towardsdatascience.com/a-comprehensive-guide-to-convolutional -neural-networks-the-eli5-way-3bd2b1164a53Accessed Jan 31, 2020]
  • "Review of Different Deep Learning Approaches for Image Classification", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 3, page no.378-384, March-2019
  • Aishwarya,” Introduction to Recurrent Neural Network”, Available: https://www.geeksforgeeks.org/introduction-to-recurrent-neural-network/Accessed Jan 31, 2020]
  • Long ??,” Recurrent Neural Network And Long-Short Term Memory”, Available: https://ai.hblab.vn/2019/04/recurrent-neural-network-and-long-short.htmlAccessed Jan 31, 2020]
  • Arunava,”ConvolutionalNeuralNetwork“,Available:https://towardsdatascience.com/convolutional-neural-network-17fb77e76c05 Accessed Jan 31, 2020]
  • Mitchell, Ross; Young, Travas; Bachleda, Bellamie; Karchmer, Michael (2006). "How Many People Use ASL in the United States?: Why Estimates Need Updating" (PDF). Sign Language Studies (Gallaudet University Press.) 6 (3). ISSN 0302-1475. Retrieved November 27, 2012.
  • Y. Jia. Caffe: An open source convolutional architecture for fast feature embedding. http://caffe.berkeleyvision.org/, 2014.Lifeprint.com. American Sign Language (ASL) Manual Alphabet (fingerspelling) 2007
  • J. Atwood, M. Eicholtz, and J. Farrell. American Sign Language Recognition System. Artificial Intelligence and Machine Learning for Engineering Design. Dept. of Mechanical Engineering, Carnegie Mellon University, 2012
    • " target="_blank">RIS     |
  • Aditi Kalsh, N.S Garewal, Sign Language Recognition System, International Journal of Computational Engineering Research, pp. 15-21, vol. 3.”.
  • J Singha, K DasIndian “Sign Language Recognition Using Eigen Value Weighted Euclidean Distance Based Classification Technique.” arXiv preprint arXiv:1303.0634, 4 (2) (2013), pp. 188-195
  • Copyright © William Vicars, Sign Language resources at LifePrint.com,http://lifeprint.com/asl101/topics/wallpaper1.htm Accessed Jan 26, 2020]
  • Kar, Aradhana and Pinaki Sankar Chatterjee. “A Video-based Approach for Translating Sign Language to Simple Sentence in English.” (2010).
  • A. S. Nikam and A. G. Ambekar, "Sign language recognition using image based hand gesture recognition techniques," 2016 Online International Conference on Green Engineering and Technologies (IC-GET), Coimbatore,2016,pp.1-5.doi: 10.1109/GET.2016.7916786
  • M P, Paulraj & Yaacob, Sazali & Zanar Azalan, Mohd Shuhanaz & Palaniappan, Rajkumar. (2010). A phoneme based sign language recognition system using skin color segmentation. 1 - 5. 10.1109/CSPA.2010.5545253.
  • Rakesh.B.S, Tamilarasan.S, Avinash N, “Hand Gesture Recognition based on Real-time Indian Sign Language,” International Journal of Computer Sciences and Engineering, Vol.7, Issue.7, pp.181-185, 2019.
  • Sanil Jain and K.V.Sameer Raja,“Indian Sign Language Character Recognition”,.Available:https://cse.iitk.ac. in/users/cs365/2015/_submissions/vinsam/report.pdf Accessed Jan 16, 2020].
  • Andrej Karpathy,”CS231n: Convolutional Neural NetworksforVisualRecognition.”,Available: http://cs231n.github.io/convolutionalnetworks/ Accessed Jan 31, 2020]
  • D. Anbarasan | R. Aravind | K. Alice "GRS – Gesture based Recognition System for Indian Sign Language Recognition System for Deaf and Dumb People" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470,Volume-2Issue-2Februar2018,
  • Sumit saha,”A Comprehensive Guide to Convolutional NeuralNetworktheELI5way.”,Available: https://towardsdatascience.com/a-comprehensive-guide-to-convolutional -neural-networks-the-eli5-way-3bd2b1164a53Accessed Jan 31, 2020]
  • "Review of Different Deep Learning Approaches for Image Classification", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 3, page no.378-384, March-2019
  • Aishwarya,” Introduction to Recurrent Neural Network”, Available: https://www.geeksforgeeks.org/introduction-to-recurrent-neural-network/Accessed Jan 31, 2020]
  • Long ??,” Recurrent Neural Network And Long-Short Term Memory”, Available: https://ai.hblab.vn/2019/04/recurrent-neural-network-and-long-short.htmlAccessed Jan 31, 2020]
  • Arunava,”ConvolutionalNeuralNetwork“,Available:https://towardsdatascience.com/convolutional-neural-network-17fb77e76c05 Accessed Jan 31, 2020]
  • Mitchell, Ross; Young, Travas; Bachleda, Bellamie; Karchmer, Michael (2006). "How Many People Use ASL in the United States?: Why Estimates Need Updating" (PDF). Sign Language Studies (Gallaudet University Press.) 6 (3). ISSN 0302-1475. Retrieved November 27, 2012.
  • Y. Jia. Caffe: An open source convolutional architecture for fast feature embedding. http://caffe.berkeleyvision.org/, 2014.Lifeprint.com. American Sign Language (ASL) Manual Alphabet (fingerspelling) 2007
  • J. Atwood, M. Eicholtz, and J. Farrell. American Sign Language Recognition System. Artificial Intelligence and Machine Learning for Engineering Design. Dept. of Mechanical Engineering, Carnegie Mellon University, 2012
    • " target="_blank">CSV

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