Comprehensive Survey on Python-Based Voice Assistants with Emphasis on JARVIS

Voice assistants have gained a significant role in the contemporary technology and they enable users to manage the gadget, search and retrieve information and to execute business through simple vocal instructions. This questionnaire is devoted to Python-based voice assistants, the special attention is paid to JARVIS which is expected to be modular, flexible, and simple to extend. JARVIS is based on the speech recognition, natural language understanding, and an SQLite database, which interprets the commands given by the user and performs system functions. The paper describes the way voice assistants translate the speech to text, the intent of the user, the response provided, and correction in case of errors in real time. It further compares JARVIS with other popular assistants like the Google Assistant, Siri, Alexa and Mycroft AI and points out differences in accuracy, offline functionality, customisation and system integration. A number of challenges of JARVIS are pointed out, such as unreliable wake-word detection, generation of redundant database files, and unreliable speech recognition under noisy conditions. These problems make it less reliable and usable. Lastly, the survey indicates possible enhancements including the creation of wake-word models, improvements in error-handling, streamlining database operations, and increased on-device intelligence to produce a more reliable, correct and scalable Python based voice assistant.