International Journal of Science, Engineering and TechnologyAuthors: Surendra Mahendra Kamble, Atharv Ganesh Hande, Sumit Vaman Ghatul, Professor Abhishek, Popat Bangar
Abstract: Artificial intelligence (AI) has drastically changed the way humans and computers interact. Deep learning architectures particularly transformer-based model have played a major role in revolutionising spoken language understanding, intent classification and generative response generation. The paper designs, implements and evaluates JARVIS AI, a personal voice assistant written in Python using a range of advanced AI techniques. The system is composed of various intelligent modules including speech recognition, natural language processing (NLP), desktop automation, real-time web search, and AI-based image generation. In the quiet condition, the performance of the Proposed system works very good. It achieves 94.7% speech recognition accuracy. The average response time for command is less than 500 ms and 96.1% successful task execution rate with 10 functionalities [1,2]. JARVIS AI has a modular architecture that allows for easy scalability, flexibility, and integration of new features JARVIS AI enables robust offline use and with deep-software automation unlike commercial cloud-based systems. The findings of the experiments show that JARVIS can be an efficient, robust and user-friendly digital assistant who can enhance one’s personal and professional productivity significantly.
