Translation of Indian Sign Language to Text-A Comprehensive Review

Authors

  • Seema Sabharwal Department of Computer Science and Engineering, Baba Mastnath University, Rohtak, INDIA
  • Priti Singla Department of Computer Science and Engineering, Baba Mastnath University, Rohtak, INDIA

Keywords:

Comprehensive review, ISL Translation, ISL Recognition, Indian Sign Language, PRISMA

Abstract

Deaf and mute persons across the world uses gestures, non-manual features to interact with fellow persons. This way of communication is called Gesture language or Sign language. Gesture languages are local in nature because of their dependency on geographical area, syntax, pragmatics, and other attributes. The focus of this paper is to present a comprehensive review of conventional as well as contemporary Indian sign language translation system. The process of literature review has been carried out in accordance with Preferred Reporting Items for Systematic reviews and Meta Analysis (PRISMA) guidelines by searching in Scopus, google scholar, Science direct and Lensorg databases. Different articles were included between the years 2010 to 2023 for the purpose of literature review. The study was based on four themes-dataset, technique, result and previous literature reviews. This is the first detailed review conducted in the field of Indian sign language translation system which solely analyses literature related to ISL as per author’s knowledge. The findings of this research article may contribute to gain insights and form a blueprint for future areas in the arena of Indian Sign Language translation/recognition system.

Downloads

Download data is not yet available.

References

A. Wadhawan and P. Kumar, “Sign Language Recognition Systems: A Decade Systematic Literature Review,” Arch. Comput. Methods Eng., vol. 28, no. 3, pp. 785–813, May 2021, doi: 10.1007/s11831-019-09384-2.

S. M. Kamal, Y. Chen, S. Li, X. Shi, and J. Zheng, “Technical Approaches to Chinese Sign Language Processing: A Review,” IEEE Access, vol. 7, pp. 96926–96935, 2019, doi: 10.1109/ACCESS.2019.2929174.

ISLRTC, “History | Indian Sign Language Research and Training Center (ISLRTC), Government of India,” Indian Sign Language Research and Training Center (ISLRTC). Accessed: Feb. 14, 2022. [Online]. Available: http://islrtc.nic.in/history-0

S. Sabharwal and P. Singla, “Indian Sign Language Digit Translation Using CNN with Swish Activation Function,” in Key Digital Trends Shaping the Future of Information and Management Science, vol. 671, in Lecture Notes in Networks and Systems, vol. 671. , Cham: Springer International Publishing, 2023, pp. 245–253. doi: 10.1007/978-3-031-31153-6_21.

I. A. Adeyanju, O. O. Bello, and M. A. Adegboye, “Machine learning methods for sign language recognition: A critical review and analysis,” Intell. Syst. Appl., vol. 12, p. 200056, Nov. 2021, doi: 10.1016/j.iswa.2021.200056.

Seema and P. Singla, “A Comprehensive Review of CNN-Based Sign Language Translation System,” in Proceedings of Data Analytics and Management, vol. 572, A. Khanna, Z. Polkowski, and O. Castillo, Eds., in Lecture Notes in Networks and Systems, vol. 572. , Singapore: Springer Nature Singapore, 2023, pp. 347–362. doi: 10.1007/978-981-19-7615-5_31.

A. Liberati et al., “The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate healthcare interventions: explanation and elaboration,” BMJ, vol. 339, no. jul21 1, pp. b2700–b2700, Dec. 2009, doi: 10.1136/bmj.b2700.

Daleesha M Viswanathan and Sumam Mary Idicula, “Recent Developments in Indian Sign Language Recognition: An Analysis,” International Journal of Computer Science and Information Technologies, vol. 6, no. 1, pp. 289–293, 2015.

M. R. K, H. Kaur, S. K. Bedi, and M. A. Lekhana, “Image-based Indian Sign Language Recognition: A Practical Review using Deep Neural Networks.” arXiv, Apr. 28, 2023. Accessed: Sep. 18, 2023. [Online]. Available: http://arxiv.org/abs/2304.14710

Anuja V. Nair and Bindu V., “A Review on Indian Sign Language Recognition,” ijca, vol. 73, no. 22, pp. 33–38, 2013.

V. K. Verma, S. Srivastava, and N. Kumar, “A comprehensive review on automation of Indian sign language,” International Conference on Advances in Computer Engineering and Applications, ICACEA 2015, 2015, pp. 138–142. doi: 10.1109/ICACEA.2015.7164682.

A. Tyagi and S. Bansal, “Feature extraction technique for vision-based Indian sign language recognition system: A review,” Advances in Intelligent Systems and Computing, 2021, pp. 39–53. doi: 10.1007/978-981-15-6876-3_4.

B. Samal and M. Panda, “Integrative review on vision-based dynamic Indian sign language recognition systems,” 1st Odisha International Conference on Electrical Power Engineering, Communication and Computing Technology, ODICON 2021, 2021. doi: 10.1109/ODICON50556.2021.9429002.

S. Das, S. K. Biswas, M. Chakraborty, and B. Purkayastha, “Intelligent Indian Sign Language Recognition Systems: A Critical Review,”Lecture Notes in Networks and Systems, 2022, pp. 703–713. doi: 10.1007/978-981-16-5987-4_71.

A. Singh, S. K. Singh, and A. Mittal, “A Review on Dataset Acquisition Techniques in Gesture Recognition from Indian Sign Language,” in Lecture Notes on Data Engineering and Communications Technologies, vol. 106, 2022, pp. 305–313. doi: 10.1007/978-981-16-8403-6_27.

Rakesh Savant and Dr. Jitendra Nasriwala, “INDIAN SIGN LANGUAGE RECOGNITION SYSTEM: APPROACHES AND CHALLENGES,” International Journal of Advance and Innovative Research, vol. 6, no. 3(IV), pp. 76–84, 2019.

A. Nandy, J. S. Prasad, S. Mondal, P. Chakraborty, and G. C. Nandi, “Recognition of Isolated Indian Sign Language Gesture in Real Time,” in Information Processing and Management, vol. 70, V. V. Das, R. Vijayakumar, N. C. Debnath, J. Stephen, N. Meghanathan, S. Sankaranarayanan, P. M. Thankachan, F. L. Gaol, and N. Thankachan, Eds., in Communications in Computer and Information Science, vol. 70. , Berlin, Heidelberg: Springer Berlin Heidelberg, 2010, pp. 102–107. doi: 10.1007/978-3-642-12214-9_18.

A. Sridhar, R. G. Ganesan, P. Kumar, and M. Khapra, “INCLUDE: A Large Scale Dataset for Indian Sign Language Recognition,” in Proceedings of the 28th ACM International Conference on Multimedia, Seattle WA USA: ACM, Oct. 2020, pp. 1366–1375. doi: 10.1145/3394171.3413528.

E. R, “ISL-CSLTR: Indian Sign Language Dataset for Continuous Sign Language Translation and Recognition.” Mendeley, Jan. 22, 2021. doi: 10.17632/KCMPDXKY7P.

E. R, “ISLAN.” Mendeley, Jan. 08, 2021. doi: 10.17632/RC349J45M5.1.

Adithya Venugopalan, “A Video Dataset of the Hand Gestures of Indian Sign Language Words used in Emergency Situations.” Mendeley, Aug. 27, 2021. doi: 10.17632/2VFDM42337.1.

K. Mistree, D. Thakor, and B. Bhatt, “Towards Indian Sign Language Sentence Recognition using INSIGNVID: Indian Sign Language Video Dataset,” Int. J. Adv. Comput. Sci. Appl., vol. 12, no. 8, 2021, doi: 10.14569/IJACSA.2021.0120881.

D. Kothadiya, C. Bhatt, K. Sapariya, K. Patel, A.-B. Gil-González, and J. M. Corchado, “Deepsign: Sign Language Detection and Recognition Using Deep Learning,” Electronics, vol. 11, no. 11, p. 1780, Jun. 2022, doi: 10.3390/electronics11111780.

“Results The Lens - Free & Open Patent and Scholarly Search,” The Lens - Free & Open Patent and Scholarly Search. Accessed: Sep. 18, 2023. [Online]. Available: https://www.lens.org/lens

J. Rekha, J. Bhattacharya, and S. Majumder, “Shape, texture and local movement hand gesture features for Indian Sign Language recognition,” in 3rd International Conference on Trendz in Information Sciences & Computing (TISC2011), Chennai, India: IEEE, Dec. 2011, pp. 30–35. doi: 10.1109/TISC.2011.6169079.

S. C. Agrawal, A. S. Jalal, and C. Bhatnagar, “Recognition of Indian Sign Language using feature fusion,” in 2012 4th International Conference on Intelligent Human Computer Interaction (IHCI), Kharagpur, India: IEEE, Dec. 2012, pp. 1–5. doi: 10.1109/IHCI.2012.6481841.

J. Singha and K. Das, “Indian Sign Language Recognition Using Eigen Value Weighted Euclidean Distance Based Classification Technique,” Int. J. Adv. Comput. Sci. Appl., vol. 4, no. 2, 2013, doi: 10.14569/IJACSA.2013.040228.

R. Sreemathy, M. Turuk, I. Kulkarni, and S. Khurana, “Sign language recognition using artificial intelligence,” Educ. Inf. Technol., Nov. 2022, doi: 10.1007/s10639-022-11391-z.

A. Kumar and R. Kumar, “A novel approach for ISL alphabet recognition using Extreme Learning Machine,” Int. J. Inf. Technol. Singap., vol. 13, no. 1, pp. 349–357, 2021, doi: 10.1007/s41870-020-00525-6.

U. Nandi, A. Ghorai, M. M. Singh, C. Changdar, S. Bhakta, and R. Kumar Pal, “Indian sign language alphabet recognition system using CNN with diffGrad optimizer and stochastic pooling,” Multimed. Tools Appl., pp. 1–22, Jan. 2022, doi: 10.1007/s11042-021-11595-4.

H. Bhavsar and Dr. J. Trivedi, “Indian Sign Language Alphabets Recognition from Static Images Using Correlation-Coefficient Algorithm with Neuro-Fuzzy Approach,” SSRN Electron. J., 2019, doi: 10.2139/ssrn.3421685.

T. S. Abraham, S. P. Sachin Raj, A. Yaamini, and B. Divya, “Transfer learning approaches in deep learning for Indian sign language classification,” Journal of Physics: Conference Series, 2022. doi: 10.1088/1742-6596/2318/1/012041.

A. K. Sahoo, M. Sharma, and R. Pal, “INDIAN SIGN LANGUAGE RECOGNITION USING NEURAL NETWORKS AND KNN CLASSIFIERS,” ARPN, vol. 9, no. 8, pp. 1255–1259, Aug. 2014.

J. Gangrade, J. Bharti, and A. Mulye, “Recognition of Indian Sign Language Using ORB with Bag of Visual Words by Kinect Sensor,” IETE J. Res., vol. 68, no. 4, pp. 2953–2967, Jul. 2022, doi: 10.1080/03772063.2020.1739569.

D. Deora and N. Bajaj, “Indian sign language recognition,” in 2012 1st International Conference on Emerging Technology Trends in Electronics, Communication & Networking, Surat, Gujarat, India: IEEE, Dec. 2012, pp. 1–5. doi: 10.1109/ET2ECN.2012.6470093.

V. Adithya, P. R. Vinod, and U. Gopalakrishnan, “Artificial neural network based method for Indian sign language recognition,” in 2013 IEEE CONFERENCE ON INFORMATION AND COMMUNICATION TECHNOLOGIES, Thuckalay, Tamil Nadu, India: IEEE, Apr. 2013, pp. 1080–1085. doi: 10.1109/CICT.2013.6558259.

Geetha M and Manjusha U C, “A Vision Based Recognition of Indian Sign Language Alphabets and Numerals Using B-Spline Approximation,” International Journal on Computer Science and Engineering (IJCSE), vol. 4, no. 3, pp. 406–415, 2012.

G. K. Kharate and A. S. Ghotkar, “Vision based multi-feature hand gesture recognition for indian sign language manual signs,” Int. J. Smart Sens. Intell. Syst., vol. 9, no. 1, pp. 124–147, 2016, doi: 10.21307/ijssis-2017-863.

S. Katoch, V. Singh, and U. S. Tiwary, “Indian Sign Language recognition system using SURF with SVM and CNN,” Array, vol. 14, p. 100141, Jul. 2022, doi: 10.1016/j.array.2022.100141.

T. Raghuveera, R. Deepthi, R. Mangalashri, and R. Akshaya, “A depth-based Indian Sign Language recognition using Microsoft Kinect,” Sādhanā, vol. 45, no. 1, p. 34, Dec. 2020, doi: 10.1007/s12046-019-1250-6.

K. Mehrotra, A. Godbole, and S. Belhe, “Indian Sign Language Recognition Using Kinect Sensor,” in Image Analysis and Recognition, vol. 9164, M. Kamel and A. Campilho, Eds., in Lecture Notes in Computer Science, vol. 9164. , Cham: Springer International Publishing, 2015, pp. 528–535. doi: 10.1007/978-3-319-20801-5_59.

Geetha M, Manjusha C, Unnikrishnan P, and Harikrishnan R, “A vision based dynamic gesture recognition of Indian Sign Language on Kinect based depth images,” in 2013 International Conference on Emerging Trends in Communication, Control, Signal Processing and Computing Applications (C2SPCA), Bangalore, India: IEEE, Oct. 2013, pp. 1–7. doi: 10.1109/C2SPCA.2013.6749448.

A. Nandy, S. Mondal, J. S. Prasad, P. Chakraborty, and G. C. Nandi, “Recognizing & interpreting Indian Sign Language gesture for Human Robot Interaction,” in 2010 International Conference on Computer and Communication Technology (ICCCT), Allahabad, Uttar Pradesh, India: IEEE, Sep. 2010, pp. 712–717. doi: 10.1109/ICCCT.2010.5640434.

W. Ahmed, K. Chanda, and S. Mitra, “Vision based Hand Gesture Recognition using Dynamic Time Warping for Indian Sign Language,” in 2016 International Conference on Information Science (ICIS), Kochi, India: IEEE, Aug. 2016, pp. 120–125. doi: 10.1109/INFOSCI.2016.7845312.

D. K. Singh, “3D-CNN based Dynamic Gesture Recognition for Indian Sign Language Modeling,” in Procedia Computer Science, 2021, pp. 76–83. doi: 10.1016/j.procs.2021.05.071.

B. Subramanian, B. Olimov, S. M. Naik, S. Kim, K.-H. Park, and J. Kim, “An integrated mediapipe-optimized GRU model for Indian sign language recognition,” Sci. Rep., vol. 12, no. 1, p. 11964, Jul. 2022, doi: 10.1038/s41598-022-15998-7.

P. C. Badhe and V. Kulkarni, “Indian sign language translator using gesture recognition algorithm,” in IEEE International Conference on Computer Graphics, Vision and Information Security (CGVIS), Bhubaneswar, India: IEEE, 2016, pp. 195–200. doi: 10.1109/CGVIS.2015.7449921.

J. L. Raheja, A. Mishra, and A. Chaudhary, “Indian sign language recognition using SVM,” Pattern Recognit. Image Anal., vol. 26, no. 2, pp. 434–441, Apr. 2016, doi: 10.1134/S1054661816020164.

P. K. Athira, C. J. Sruthi, and A. Lijiya, “A Signer Independent Sign Language Recognition with Co-articulation Elimination from Live Videos: An Indian Scenario,” J. King Saud Univ. - Comput. Inf. Sci., vol. 34, no. 3, pp. 771–781, Mar. 2022, doi: 10.1016/j.jksuci.2019.05.002.

A. M. Deshpande, G. Inamdar, R. Kankaria, and S. Katage, “A Deep Learning Framework for Real-Time Indian Sign Language Gesture Recognition and Translation to Text and Audio,” in Proceedings of the 6th International Conference on Advance Computing and Intelligent Engineering, vol. 428, B. Pati, C. R. Panigrahi, P. Mohapatra, and K.-C. Li, Eds., in Lecture Notes in Networks and Systems, vol. 428. , Singapore: Springer Nature Singapore, 2023, pp. 287–300. doi: 10.1007/978-981-19-2225-1_26.

S. Paul, M. Jajoo, A. Raj, A. F. Mollah, M. Nasipuri, and S. Basu, “Dynamic Hand Gesture Recognition of the Days of a Week in Indian Sign Language Using Low-Cost Depth Device,” in Intelligent Data Engineering and Analytics, vol. 266, S. C. Satapathy, P. Peer, J. Tang, V. Bhateja, and A. Ghosh, Eds., in Smart Innovation, Systems and Technologies, vol. 266. , Singapore: Springer Nature Singapore, 2022, pp. 141–149. doi: 10.1007/978-981-16-6624-7_15.

M. Daniel Nareshkumar and B. Jaison, “A Light-Weight Deep Learning-Based Architecture for Sign Language Classification,” Intell. Autom. Soft Comput., vol. 35, no. 3, pp. 3501–3515, 2023, doi: 10.32604/iasc.2023.027848.

K. Tripathi and N. B. G. C. Nandi, “Continuous Indian Sign Language Gesture Recognition and Sentence Formation,” Procedia Comput. Sci., vol. 54, pp. 523–531, 2015, doi: 10.1016/j.procs.2015.06.060.

A. K, P. P, and R. C. Poonia, “LiST: A Lightweight Framework for Continuous Indian Sign Language Translation,” Information, vol. 14, no. 2, p. 79, Jan. 2023, doi: 10.3390/info14020079.

K. Tripathi, N. Baranwal, and G. C. Nandi, “Continuous dynamic Indian Sign Language gesture recognition with invariant backgrounds,” in 2015 International Conference on Advances in Computing, Communications and Informatics (ICACCI), Kochi, India: IEEE, Aug. 2015, pp. 2211–2216. doi: 10.1109/ICACCI.2015.7275945.

A. Mittal, P. Kumar, P. P. Roy, R. Balasubramanian, and B. B. Chaudhuri, “A Modified LSTM Model for Continuous Sign Language Recognition Using Leap Motion,” IEEE Sens. J., vol. 19, no. 16, pp. 7056–7063, Aug. 2019, doi: 10.1109/JSEN.2019.2909837.

N. Baranwal and G. C. Nandi, “An efficient gesture based humanoid learning using wavelet descriptor and MFCC techniques,” Int. J. Mach. Learn. Cybern., vol. 8, no. 4, pp. 1369–1388, 2017, doi: 10.1007/s13042-016-0512-4.

H. Muthu Mariappan and V. Gomathi, “Real-time recognition of Indian sign language,” ICCIDS 2019 - 2nd International Conference on Computational Intelligence in Data Science, Proceedings, 2019. doi: 10.1109/ICCIDS.2019.8862125.

K. Shenoy, T. Dastane, V. Rao, and D. Vyavaharkar, “Real-time Indian Sign Language (ISL) Recognition,” 9th International Conference on Computing, Communication and Networking Technologies, ICCCNT 2018, 2018. doi: 10.1109/ICCCNT.2018.8493808.

P. V. V. Kishore and P. Rajesh Kumar, “A Video Based Indian Sign Language Recognition System (INSLR) Using Wavelet Transform and Fuzzy Logic,” Int. J. Eng. Technol., vol. 4, no. 5, pp. 537–542, 2012, doi: 10.7763/IJET.2012.V4.427.

Downloads

Published

02.02.2024

How to Cite

Sabharwal, S. ., & Singla, P. . (2024). Translation of Indian Sign Language to Text-A Comprehensive Review. International Journal of Intelligent Systems and Applications in Engineering, 12(14s), 309–319. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/4667

Issue

Vol. 12 No. 14s (2024)

Section

Research Article

License

Creative Commons License

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

All papers should be submitted electronically. All submitted manuscripts must be original work that is not under submission at another journal or under consideration for publication in another form, such as a monograph or chapter of a book. Authors of submitted papers are obligated not to submit their paper for publication elsewhere until an editorial decision is rendered on their submission. Further, authors of accepted papers are prohibited from publishing the results in other publications that appear before the paper is published in the Journal unless they receive approval for doing so from the Editor-In-Chief.

IJISAE open access articles are licensed under a Creative Commons Attribution-ShareAlike 4.0 International License. This license lets the audience to give appropriate credit, provide a link to the license, and indicate if changes were made and if they remix, transform, or build upon the material, they must distribute contributions under the same license as the original.