AI Sign Language Detection for Disabled People & Chatbot

Abstract - This project presents an intelligent, multi-functional system designed to empower and support individuals with disabilities, especially those with hearing or speech impairments. The solution integrates real-time Sign Language Detection with an AI-powered assistant to facilitate seamless communication, access to essential services, and daily digital interactions. Built using HTML, CSS, JavaScript, and machine learning techniques, this innovative platform bridges the communication gap between differently-abled users and the digital world. The system uses computer vision models to recognize sign language gestures, particularly the English alphabet, enabling users to communicate through hand signs. The recognized signs are then translated into text or voice using Text-to-Speech (TTS) modules. To extend usability, this feature is integrated into a user-friendly graphical interface that allows users to interact with the system visually and audibly. A major highlight of the project is its Jarvis-inspired voice assistant, which responds to the wake word "Hey Jarvis." Once activated, the assistant can perform various tasks such as opening websites, fetching real-time information (e.g., weather, news, etc.), and responding to queries using a smart chatbot module. The chatbot fetches accurate responses from the Google Search API to ensure up-to-date and contextually relevant answers.

Authors

Publication Details

Journal
INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT
Published
2025-04-24
DOI
https://doi.org/10.55041/ijsrem45854
Primary Topic
Hand Gesture Recognition Systems
Type
article
Field-Weighted Citation Impact
0.00
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article

AI Sign Language Detection for Disabled People & Chatbot

Chaitali Mane
INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT
Hand Gesture Recognition Systems
article

AI Sign Language Detection for Disabled People & Chatbot

Chaitali Mane
article en

Abstract

Abstract - This project presents an intelligent, multi-functional system designed to empower and support individuals with disabilities, especially those with hearing or speech impairments. The solution integrates real-time Sign Language Detection with an AI-powered assistant to facilitate seamless communication, access to essential services, and daily digital interactions. Built using HTML, CSS, JavaScript, and machine learning techniques, this innovative platform bridges the communication gap between differently-abled users and the digital world. The system uses computer vision models to recognize sign language gestures, particularly the English alphabet, enabling users to communicate through hand signs. The recognized signs are then translated into text or voice using Text-to-Speech (TTS) modules. To extend usability, this feature is integrated into a user-friendly graphical interface that allows users to interact with the system visually and audibly. A major highlight of the project is its Jarvis-inspired voice assistant, which responds to the wake word "Hey Jarvis." Once activated, the assistant can perform various tasks such as opening websites, fetching real-time information (e.g., weather, news, etc.), and responding to queries using a smart chatbot module. The chatbot fetches accurate responses from the Google Search API to ensure up-to-date and contextually relevant answers.

INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENTVol. 09(04)
Openalex Percentile: Top 93%
Hand Gesture Recognition Systems
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