Bridging communication gaps: An AI-powered real-time system for sign language, speech and text translation

Communication effectiveness poses an essential challenge to the millions who have hearing or speech impairments in their lives. HandSpeak provides a real-time AI interface through which users can interact easily because it transforms sign language into written messages and spoken words. The Sign-to-Speech module performs its functions through the integration of 3D cameras with Convolutional Neural Networks (CNNs) as well as Long Short-Term Memory (LSTM) networks to detect hand landmarks while tracking hand movements and interpreting sign gesture temporal sequences. Speech input flows through the Speech-to-Sign module to produce text output that gets processed into animated sign language expressions under AI avatar operations. Transformers boost linguistic precision and the integration between Django and Flask provides users with an optimized web-based interface. The application uses SQLite for optimized data storage together with Blender for producing sign animations. The technology serves to create an barrier-free environment for natural communication which enhances inclusivity while providing better accessibility to hearing and speech disabled people in various social and professional environments.

Authors

Publication Details

Journal
International Journal of Science and Research Archive
Published
2025-03-30
DOI
https://doi.org/10.30574/ijsra.2025.14.3.0807
Primary Topic
Hand Gesture Recognition Systems
Type
article
Field-Weighted Citation Impact
0.00
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article

Bridging communication gaps: An AI-powered real-time system for sign language, speech and text translation

Naga Sasha Lakshmi Pokanati, Monika Devi Imandi, Yamini Sariki, Sivaram Sangula et al.
International Journal of Science and Research Archive
Hand Gesture Recognition Systems
article

Bridging communication gaps: An AI-powered real-time system for sign language, speech and text translation

Naga Sasha Lakshmi Pokanati, Monika Devi Imandi, Yamini Sariki, Sivaram Sangula, Nagendra Vasamsetti
article en

Abstract

Communication effectiveness poses an essential challenge to the millions who have hearing or speech impairments in their lives. HandSpeak provides a real-time AI interface through which users can interact easily because it transforms sign language into written messages and spoken words. The Sign-to-Speech module performs its functions through the integration of 3D cameras with Convolutional Neural Networks (CNNs) as well as Long Short-Term Memory (LSTM) networks to detect hand landmarks while tracking hand movements and interpreting sign gesture temporal sequences. Speech input flows through the Speech-to-Sign module to produce text output that gets processed into animated sign language expressions under AI avatar operations. Transformers boost linguistic precision and the integration between Django and Flask provides users with an optimized web-based interface. The application uses SQLite for optimized data storage together with Blender for producing sign animations. The technology serves to create an barrier-free environment for natural communication which enhances inclusivity while providing better accessibility to hearing and speech disabled people in various social and professional environments.

International Journal of Science and Research ArchiveVol. 14(3)
Openalex Percentile: Top 95%
Hand Gesture Recognition Systems
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Bridging communication gaps: An AI-powered real-time system for sign language, speech and text translation — Naga Sasha Lakshmi Pokanati, Monika Devi Imandi, et al. · International Journal of Science and Research Archive (2025) | TGRS Research Map | TGRS