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

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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Publication Details

Journal
International Research Journal on Advanced Engineering Hub (IRJAEH)
Published
2025-03-19
DOI
https://doi.org/10.47392/irjaeh.2025.0079
Primary Topic
Hand Gesture Recognition Systems
Type
article
Field-Weighted Citation Impact
0.00
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article

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

S. Tiwari, Arnab Kumar Mishra, Kshitij Kumar Singh, Rashmi Maheshwari
International Research Journal on Advanced Engineering Hub (IRJAEH)
Hand Gesture Recognition Systems
article

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

S. Tiwari, Arnab Kumar Mishra, Kshitij Kumar Singh, Rashmi Maheshwari
article en

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.

International Research Journal on Advanced Engineering Hub (IRJAEH)Vol. 3(03)
Dwarkadas J. Sanghvi College of Engineering (IN)
Quality Education
Openalex Percentile: Top 96%
Hand Gesture Recognition Systems
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