SIGN TO SPEECH CONVERSION AND HOME AUTOMATION SYSTEM

Authors

  • Dr. Madhavi Patil Asst. Prof, E&TC, SSWCOE, Solapur
  • Ms. Pooja Biradar B. Tech E&TC
  • Ms. Ankita Dindore B. Tech E&TC
  • Ms. Rupali Angule B. Tech E&TC
  • Ms. Saraswati Limbute B. Tech E&TC

DOI:

https://doi.org/10.26662/31xtqk37

Keywords:

Sign language, speech synthesis, gesture recognition, home automation, computer vision, IoT, CNN.

Abstract

The growing demand for inclusive technologies has driven research into systems that bridge the communication gap between differently-abled individuals and the wider community. This paper presents an integrated system that interprets sign language into speech and simultaneously enables control over smart home appliances. The system utilizes computer vision for gesture recognition using convolutional neural networks (CNNs), speech synthesis for voice output, and IoT-based architecture for home automation. The proposed system enhances accessibility, independence, and inclusivity for individuals with speech and hearing impairments.

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Published

2025-07-11

Issue

Vol. 11 No. 7 (2025): Journalnx

Section

Articles

License

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

How to Cite

SIGN TO SPEECH CONVERSION AND HOME AUTOMATION SYSTEM. (2025). JournalNX - A Multidisciplinary Peer Reviewed Journal, 11(7), 1-5. https://doi.org/10.26662/31xtqk37