INTERNATIONAL JOURNAL OF ADVANCE RESEARCH IN ULTIDISCIPLINARY

This project implements a basic voice-activated assistant, named Jarvis, using Python. The assistant listens for a predefined wake word ("Jarvis") through speech recognition, allowing users to issue voice commands. Upon activation, it can perform a variety of tasks, such as opening and closing commonly used software (e.g., Chrome, Microsoft Edge, Notepad, Calculator), telling the current time, and playing YouTube videos via the pywhatkit library.The system utilizes the speech_recognition library for real-time speech-to-text conversion and pyttsx3 for text-to-speech responses, enabling smooth human-computer interaction. Additionally, it leverages system commands and subprocesses to interact with the operating system for software control. Key features include continuous wake word detection, dynamic command parsing, and error handling for robust operation. The script demonstrates a simple yet effective framework for voice-controlled automation, showcasing the potential of integrating speech recognition, natural language processing, and system automation in Python.
KEYWORDS :
Voice-activated assistant, Jarvis, Speech recognition, Natural language processing (NLP), Python automation, Text-to-speech (TTS), Speech-to-text (STT), pyttsx3, pywhatkit, Wake word detection, System automation, Human-computer interaction (HCI), Voice command system, Real-time voice recognition, Operating system interaction, Software control automation, Error handling in automation, Subprocess management, Voice command parsing, Computer vision integration.