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JARVIS – PERSONAL ASSISTANT
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ABSTRACT:
In the era of artificial intelligence and automation, the development of intelligent virtual assistants has transformed human-computer interaction. This paper presents the design and implementation of Jarvis, a multifunctional personal assistant inspired by modern AI systems. Jarvis integrates natural language processing (NLP), voice interaction, and automation capabilities to execute a wide range of tasks including information retrieval, weather updates, application launching, internet searches, and system operations. Developed using Python, the assistant incorporates APIs such as OpenAI’s ChatGPT for conversational abilities and utilizes speech recognition and text-to-speech modules for hands-free control. A user-friendly graphical interface enhances accessibility, while the modular architecture ensures scalability for future enhancements. This research demonstrates the feasibility and practicality of building an affordable, intelligent assistant tailored for desktop environments, contributing to the advancement of smart personal assistant technologies.
Edtech Publishers (OPC) Private Limited
Title: JARVIS – PERSONAL ASSISTANT
Description:
ABSTRACT:
In the era of artificial intelligence and automation, the development of intelligent virtual assistants has transformed human-computer interaction.
This paper presents the design and implementation of Jarvis, a multifunctional personal assistant inspired by modern AI systems.
Jarvis integrates natural language processing (NLP), voice interaction, and automation capabilities to execute a wide range of tasks including information retrieval, weather updates, application launching, internet searches, and system operations.
Developed using Python, the assistant incorporates APIs such as OpenAI’s ChatGPT for conversational abilities and utilizes speech recognition and text-to-speech modules for hands-free control.
A user-friendly graphical interface enhances accessibility, while the modular architecture ensures scalability for future enhancements.
This research demonstrates the feasibility and practicality of building an affordable, intelligent assistant tailored for desktop environments, contributing to the advancement of smart personal assistant technologies.
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