Authors: Anish Mukhiya, Raushan Kumar Ram, Anuraj Chaudhary, Omkar Mahto
Abstract: Background: Personal Desktop Voice Assistants (PDVAs) represent a significant advancement in human-computer interaction, offering intuitive voice-based control of desktop environments. Meth- ods: This study employed Python programming language with integrated speech recognition, natural language processing, and text-to-speech technologies to develop an accessible PDVA. The system archi- tecture incorporates wake word detection, intent recognition, and task execution modules. Results: The developed PDVA successfully executes diverse commands including web searching, media control, system management, and information retrieval. The system demonstrates particular effectiveness for visually impaired users, providing multimodal feedback through synthesized speech and on-screen text. Conclu- sion: The research confirms that Python-based PDVAs can significantly enhance desktop accessibility while highlighting the importance of addressing privacy concerns and interaction limitations in future developments.
