SignoBot: A Hybrid Advance Real Time Sign Detection Tool
Aakarsh Sharma
, Akshay Mudgal , Sakshi Kathuria
Sign language Recognition, Assistive Technology, AI Chatbot, Gemini API, Accessibility, Human-Computer Interaction
The communication barriers experienced by individuals with hearing and speech impairments demand innovative and accessible technological solutions. In response to this need, SignoBot is proposed as a real-time sign language recognition and conversational AI system. SignoBot aims to integrate computer vision techniques for accurate hand gesture detection, machine learning algorithms for gesture classification, and AI-based chatbot functionalities for interactive communication. The system is designed to capture hand movements through webcam-based input, process frames using MediaPipe and custom-trained models, and translate recognized gestures into both text and speech outputs. Furthermore, it incorporates Google Gemini API to facilitate speech- and text-based queries, allowing users to interact with an AI agent seamlessly. By offering dual input modes and real-time feedback, SignoBot seeks to enhance communication assistance for individuals with physical challenges. This paper presents a comprehensive overview of the methodology, the technological components employed, and a comparative analysis with existing solutions to highlight SignoBot’s potential impact in advancing assistive communication technologies.
"SignoBot: A Hybrid Advance Real Time Sign Detection Tool", TIJER - TIJER - INTERNATIONAL RESEARCH JOURNAL (www.TIJER.org), ISSN:2349-9249, Vol.12, Issue 4, page no.b82-b86, April-2025, Available :https://tijer.org/TIJER/papers/TIJER2504151.pdf
Volume 12
Issue 4,
April-2025
Pages : b82-b86
Paper Reg. ID: TIJER_157686
Published Paper Id: TIJER2504151
Downloads: 000284
Research Area: Science and Technology
Country: Ghaziabad, Uttar Pradesh, India
ISSN: 2349-9249 | IMPACT FACTOR: 8.57 Calculated By Google Scholar | ESTD YEAR: 2014
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.57 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: TIJER (IJ Publication) Janvi Wave
