Development of Gesture-to-Voice Glove for Individuals with Speech and Hearing Impairments


Authors : Shwet Kamal; Nithyashree M; B Sudha

Volume/Issue : Volume 9 - 2024, Issue 12 - December

Google Scholar : https://tinyurl.com/zr53bw72

Scribd : https://tinyurl.com/3a4wxhss

DOI : https://doi.org/10.5281/zenodo.14591355

Abstract : This project presents the development of a cost-effective assistive device aimed at bridging the communication gap between deaf-mute individuals and the hearing community. The device is built around Smart Gloves embedded with flex and motion sensors, designed to detect hand movements corresponding to sign language gestures. These gestures are processed by a microcontroller that interprets the signals and converts them into voice output, allowing real-time verbal communication. The system integrates with a server that translates sign language into digital speech, providing an accessible and efficient communication solution. The prototype is capable of recognizing all 26 letters of the English alphabet, numbers, and commonly used words, covering a wide range of everyday communication needs. With its affordability and ease of use, the device offers a practical and economical solution for individuals with speech disabilities, making it accessible across diverse economic backgrounds. The gloves demonstrate high accuracy in recognizing gestures, ensuring reliable communication without requiring extensive training or technical skills. Although the prototype shows promising results, further testing with a more diverse set of users is recommended to assess its real-world effectiveness and optimize its performance. This solution has the potential to significantly enhance the communication experience for individuals with speech impairments.

Keywords : Gesture; Accessibility; Communication; Sensors; Speech; IoT; Recognition.

References :

  1. V. Padmanabhan, M.Sornalatha, “Hand gesture recognition and voice conversion system for dumb people,” International Journal of Scientific & Engineering Research, Volume 5, Issue 5, May-2014 427 ISSN 2229-5518
  2. Shravani Jadhav, Siddhi Mhatre, Riddhi Patil, Prof. Prachi Sorte, “Smart Hand Gloves for Deaf and Dumb People”, International Journal for Research in Applied Science & Engineering Technology (IJRASET) ISSN: 2321-9653; IC Value: 45.98; SJ Impact Factor: 7.538 Volume 12 Issue III Mar 2024
  3. Prof. Niranjan L. Bhale, Sammed Pawar, Amit Pawar, Prajwal Niphade, Kamlesh Nagare, “Smart Gloves for Dumb and Deaf People”, International Journal of Advanced Research in Science, Communication and Technology (IJARSCT) ISSN (Online) 2581-9429 Volume 3, Issue 7, May 2023
  4. Sakshi Wankhade, Vishal Wadekar, Ajinath Algude, Nagarjun Jadhav, Dr. Priya Gokhale, “SMART HAND GLOVES FOR DEAF AND DUMB”, International Research Journal of Modernization in Engineering Technology and Science e-ISSN: 2582-5208 Volume:05/Issue:05/May-2023 Impact Factor- 7.868
  5. Shastri School For Deaf and Dumb Children, 2nd Cross Rd, Shankar Nagar, Mahalakshmi Layout, Bengaluru, Karnataka-560096

This project presents the development of a cost-effective assistive device aimed at bridging the communication gap between deaf-mute individuals and the hearing community. The device is built around Smart Gloves embedded with flex and motion sensors, designed to detect hand movements corresponding to sign language gestures. These gestures are processed by a microcontroller that interprets the signals and converts them into voice output, allowing real-time verbal communication. The system integrates with a server that translates sign language into digital speech, providing an accessible and efficient communication solution. The prototype is capable of recognizing all 26 letters of the English alphabet, numbers, and commonly used words, covering a wide range of everyday communication needs. With its affordability and ease of use, the device offers a practical and economical solution for individuals with speech disabilities, making it accessible across diverse economic backgrounds. The gloves demonstrate high accuracy in recognizing gestures, ensuring reliable communication without requiring extensive training or technical skills. Although the prototype shows promising results, further testing with a more diverse set of users is recommended to assess its real-world effectiveness and optimize its performance. This solution has the potential to significantly enhance the communication experience for individuals with speech impairments.

Keywords : Gesture; Accessibility; Communication; Sensors; Speech; IoT; Recognition.

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