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Research Article
Sign Tone: Two Way Sign Language Recognition and Multilingual Interpreter System Using Deep Learning
S. Surya1
Saranya S2
Swetha R3
Hemashree G4
1Assistant Professor, Department of Information Technology, Er. Perumal Manimekalai College of Engineering, Hosur, Tamilnadu, India. 234 Department of Information Technology, Er. Perumal Manimekalai College of Engineering, Hosur, Tamilnadu, India.
Published Online: May-August 2024
Pages: 148-153
Cite this article
↗ https://www.doi.org/10.59256/indjcst.20240302022
References
1. W. Sandler and D. Lillo-Martin, Sign language and linguistic universals. Cambridge University Press, 2006.
2. Z. Yang, Z. Shi, X. Shen, and Y.-W. Tai, “Sf-net: Structured feature network for continuous sign language recognition,” arXiv preprintarXiv:1908.01341, 2019.
3. O. Koller, J. Forster, and H. Ney, “Continuous sign language recogni- tion: Towards large vocabulary statistical recognition systems
handling multiple signers,” Computer Vision and Image Understanding, vol. 141, pp. 108–125, 2015.
4. R. E. Mitchell, T. A. Young, B. BACHELDA, and M. A. Karchmer, “How many people use asl in the united states? why estimates need
updating,” Sign Language Studies, vol. 6, no. 3, pp. 306–335, 2006.
5. D. Bragg, O. Koller, M. Bellard, L. Berke, P. Boudrealt, A. Braffort,
6. N. Caselli, M. Huenerfauth, H. Kacorri, T. Verhoef et al., “Sign language recognition, generation, and translation: An interdisciplinary
perspective,” arXiv preprint arXiv:1908.08597, 2019.
7. G. T. Papadopoulos and P. Daras, “Human action recognition using 3d reconstruction data,” IEEE Transactions on Circuits and Systems
for Video Technology, vol. 28, no. 8, pp. 1807–1823, 2016.
8. C. Padden, “Verbs and role-shifting in american sign language,” in Proceedings of the fourth national symposium on sign language research and teaching, vol. 44. National Association of the Deaf Silver Spring, MD, 1986, p. 57.
9. K. Emmorey, “Space on hand: The exploitation of signing space to illustrate abstract thought.” 2001.
10. H. Cooper, B. Holt, and R. Bowden, “Sign language recognition,” in Visual Analysis of Humans. Springer, 2011, pp. 539–562.
11. F. Ronchetti, F. Quiroga, C. A. Estrebou, L. C. Lanzarini, and A. Rosete, “Lsa64: an argentinian sign language dataset,” in XXII Congreso Ar- gentino de Ciencias de la Computacio´n (CACIC 2016)., 2016.
12. M. W. Kadous et al., “Machine recognition of auslan signs using powergloves: Towards large-lexicon recognition of sign language,” in Proceedings of the Workshop on the Integration of Gesture in Language and Speech, vol. 165, 1996.
2. Z. Yang, Z. Shi, X. Shen, and Y.-W. Tai, “Sf-net: Structured feature network for continuous sign language recognition,” arXiv preprintarXiv:1908.01341, 2019.
3. O. Koller, J. Forster, and H. Ney, “Continuous sign language recogni- tion: Towards large vocabulary statistical recognition systems
handling multiple signers,” Computer Vision and Image Understanding, vol. 141, pp. 108–125, 2015.
4. R. E. Mitchell, T. A. Young, B. BACHELDA, and M. A. Karchmer, “How many people use asl in the united states? why estimates need
updating,” Sign Language Studies, vol. 6, no. 3, pp. 306–335, 2006.
5. D. Bragg, O. Koller, M. Bellard, L. Berke, P. Boudrealt, A. Braffort,
6. N. Caselli, M. Huenerfauth, H. Kacorri, T. Verhoef et al., “Sign language recognition, generation, and translation: An interdisciplinary
perspective,” arXiv preprint arXiv:1908.08597, 2019.
7. G. T. Papadopoulos and P. Daras, “Human action recognition using 3d reconstruction data,” IEEE Transactions on Circuits and Systems
for Video Technology, vol. 28, no. 8, pp. 1807–1823, 2016.
8. C. Padden, “Verbs and role-shifting in american sign language,” in Proceedings of the fourth national symposium on sign language research and teaching, vol. 44. National Association of the Deaf Silver Spring, MD, 1986, p. 57.
9. K. Emmorey, “Space on hand: The exploitation of signing space to illustrate abstract thought.” 2001.
10. H. Cooper, B. Holt, and R. Bowden, “Sign language recognition,” in Visual Analysis of Humans. Springer, 2011, pp. 539–562.
11. F. Ronchetti, F. Quiroga, C. A. Estrebou, L. C. Lanzarini, and A. Rosete, “Lsa64: an argentinian sign language dataset,” in XXII Congreso Ar- gentino de Ciencias de la Computacio´n (CACIC 2016)., 2016.
12. M. W. Kadous et al., “Machine recognition of auslan signs using powergloves: Towards large-lexicon recognition of sign language,” in Proceedings of the Workshop on the Integration of Gesture in Language and Speech, vol. 165, 1996.
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