Evaluation of an AI desktop assistant demonstrates 90 to 95 percent accuracy in differently-abled individuals, suggesting enhanced computing accessibility across diverse dialects.
In a quickly progressing digital world, the arrival of virtual assistants has become a revolutionary principle for human-computer interactions. In this research project, an AI Desktop Assistant inspired by Jarvis's concept is presented, with the focus on helping users through voice commands. Specifically, this initiative aims to address the requirements of people with disabilities and enhance the computing experiences. The Desktop Assistant seamlessly integrates speech recognition model, OpenAI GPT models, and other functionalities to provide extensive and user-friendly interactions. The architecture of the system is adequately designed to suitable users, comprising of speech recognition modules and models for turning text to speech. The desktop assistant model supports additional features, involving locating and managing files, playing music, moving mail, and storing the requests-responses made via OpenAI's API in the system. The system also supports surfing the web, allowing an environment that allows different users to use the technology efficiently and emphasize the safety of those users. The results reveal that the AI desktop model is running effectively in addressing the weaknesses of the existing models. Our model's capabilities include responding to commands while making the navigation and engagement of disabled persons. The system features a performance rate up to 90-95 percent, enabling interactions with users of varying dialect and accents.
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Karkra et al. (2024) studied this question.
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