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Stream/Area:
-
Subject:
-
Paper ID:
10.55041/IJSREM39932
Volume:
8 |
12 |
Dec 2024
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
In recent years, advancements in computer vision and natural language processing (NLP) have led to the development of highly accessible and assistive technologies. This technology leverages these advancements to create a system that provides real-time object detection and text recognition capabilities, integrated with speech synthesis for audio feedback. The system employs the YOLO (You Only Look Once) algorithm for fast and accurate object detection and an Optical Character Recognition (OCR) module for extracting text from captured images. Text-to-speech (TTS) technology is incorporated to deliver audio outputs, ensuring accessibility for users, especially those with visual impairments. This decentralized system operates on user commands and does not rely on cloud processing, ensuring faster response times and data privacy. By combining computer vision and NLP, this paper offers a cost-effective and portable solution for real-time assistive applications, empowering users to interact effectively with their surroundings through visual data processing and auditory feedback.
KEYWORDS
Publication Date
12/21/2024
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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No funding information available for this research.
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