Real-Time Gesture Recognition System for Speech Impaired People

  • Unique Paper ID: 185810
  • Volume: 12
  • Issue: no
  • PageNo: 84-89
  • Abstract:
  • In today's modern society, effective communication plays a crucial role in human interaction. However, individuals who experience speech impairments encounter considerable difficulties in expressing themselves and establishing connections with others. In response to this challenge, we introduce an innovative Real-Time Sign Gesture Recognition System tailored for individuals with speech impairments. This Proposed work is designed to empower speech-impaired individuals by facilitating seamless communication with their environment in real-time. The Sign recognition system captures the sign gestures either using camera or sensors and interpreted into meaningful sentences. Subsequently, these interpreted sentences are converted into audible speech, enabling speech-impaired individuals to participate in fluid and meaningful communication. This system useful to general people to understand the speech impaired peoples what they want to say and convey. This paper aims to explore the sign-languages and developing the real-time sign language recognition system. The background section focuses on evolution of sign language and a review of researchers in the development process. It also includes the new approach of recognizing the signs and converting them into the multilingual speech and operating the IOT devices with specific commands. In the next section it includes proposed architecture and new approach of converting sign language and controlling the IOT devices.

Copyright & License

Copyright © 2025 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

BibTeX

@article{185810,
        author = {Mr. Sahil A. Mujawar and Dr. Sangram T. Patil and Dr. Jaydeep B. Patil and Mr. Rushikesh R. Powar},
        title = {Real-Time Gesture Recognition System for Speech Impaired People},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {12},
        number = {no},
        pages = {84-89},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=185810},
        abstract = {In today's modern society, effective communication plays a crucial role in human interaction. However, individuals who experience speech impairments encounter considerable difficulties in expressing themselves and establishing connections with others. In response to this challenge, we introduce an innovative Real-Time Sign Gesture Recognition System tailored for individuals with speech impairments. This Proposed work is designed to empower speech-impaired individuals by facilitating seamless communication with their environment in real-time.
The Sign recognition system captures the sign gestures either using camera or sensors and interpreted into meaningful sentences. Subsequently, these interpreted sentences are converted into audible speech, enabling speech-impaired individuals to participate in fluid and meaningful communication. This system useful to general people to understand the speech impaired peoples what they want to say and convey.
This paper aims to explore the sign-languages and developing the real-time sign language recognition system.
The background section focuses on evolution of sign language and a review of researchers in the development process. It also includes the new approach of recognizing the signs and converting them into the multilingual speech and operating the IOT devices with specific commands. In the next section it includes proposed architecture and new approach of converting sign language and controlling the IOT devices.},
        keywords = {Computer-Vision, Convolutional Neural Network, Gesture Recognition, TTS, IOT},
        month = {},
        }

Cite This Article

  • ISSN: 2349-6002
  • Volume: 12
  • Issue: no
  • PageNo: 84-89

Real-Time Gesture Recognition System for Speech Impaired People

Related Articles