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Original Article

Sign Language Translation Platform: Automated Speech-to-Sign Production and Sign-to-Speech Recognition Using Media Pipe Technology

Ramya S1 Lakshmi J2 Chaitra M3 Hemvathi M4 Divya P5
1 Assistant Professor, Department of Information Technology, Er.Perumal Manimekalai College of Engineering, Hosur, Tamilnadu, India. 2 3 4 5 Department of Information Technology, Er.Perumal Manimekalai College of Engineering, Hosur, Tamilnadu, India.

Published Online: March-April 2026

Pages: 437-443

References

1. Media Pipe Contributors, "Media Pipe: A framework for building multimodal machine learning pipelines," Google Research, 2022. [Online]. Available: https://mediapipe.dev
2. T. Baltrusaitis, C. Zhang, and Y. Choi, "Multimodal machine learning: A survey and taxonomy," IEEE Trans. Pattern Anal. Mach. Intell., vol. 41, no. 2, pp. 423-443, 2019.
3. A. Pu, B. Woll, and K. Choo, "Sign language recognition: A comprehensive survey," ACM Comput. Surv., vol. 54, no. 7, pp. 1-37, 2021.
4. S. Hochreiter and J. Schmidhuber, "Long short-term memory," Neural Comput., vol. 9, no. 8, pp. 1735-1780, 1997.
5. A. Vaswani et al., "Attention is all you need," Adv. Neural Inf. Process. Syst., pp. 5998-6008, 2017.
6. Angular Team, "Angular: Modern web framework," 2024. [Online]. Available: https://angular.io
7. Google Cloud, "Firebase: Build better apps faster," 2024. [Online]. Available: https://firebase.google.com
8. W3C, "Web Accessibility Guidelines (WCAG) 2.1," 2018. [Online]. Available: https://www.w3.org/WAI/WCAG21/quickref/

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