Sign Speak: Sign Language-To-Speech and Speech-To-Sign Language

Authors

  • Rashmi Maheshwari Assistant Professor, Department of ECS, Shree L.R. Tiwari College of Engg., Mumbai, Maharashtra, India. Author
  • Khushi Anand Singh UG Scholar, Department of ECS, Shree L.R. Tiwari College of Engg., Mumbai, Maharashtra, India. Author
  • Shashank Jayshankar Tiwari UG Scholar, Department of ECS, Shree L.R. Tiwari College of Engg., Mumbai, Maharashtra, India. Author
  • Anuj Mukesh Mishra UG Scholar, Department of ECS, Shree L.R. Tiwari College of Engg., Mumbai, Maharashtra, India. Author

DOI:

https://doi.org/10.47392/IRJAEH.2025.0079

Keywords:

Two-Way Communication, Firebase, Flutter, TensorFlow Lite, Vision-Based Application, Natural Language Processing (NLP), Convolutional Neural Networks (CNN), Gesture Recognition, Sign Language Translation

Abstract

Exchange of words among the community is one of the essential mediums of survival. Developing a vision-based application that translates sign language into intelligible speech and vice versa is the main goal of our suggested technique [1]. The objective is to establish a link between the hearing and hearing-impaired communities and begin two-way conversation[2].This application presents the Android program that allows blind, deaf, and dumb persons to converse with one another. Utilizing technologies such as TensorFlow Lite for gesture recognition, Flutter for mobile development, and Firebase for backend support, the application guarantees flexibility and inclusivity. CNNs and natural language processing (NLP) improve speech and gesture recognition, and offline functionality fixes connectivity problems.

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Published

2025-03-19

How to Cite

Sign Speak: Sign Language-To-Speech and Speech-To-Sign Language. (2025). International Research Journal on Advanced Engineering Hub (IRJAEH), 3(03), 563-569. https://doi.org/10.47392/IRJAEH.2025.0079

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