Transforming User Engagement Through Smart AI Desktop Assistant

Authors

  • Mamatha Talakoti
  • A Bala Ram
  • Dhanamma Jagli
  • Paray Navya Sree
  • Konde Pranitha
  • Appani Madhavi

Keywords:

Voice Assistant, Neural Networks, Google Search, Speech Recognition, Artificial Intelligence, Natural Language Processing, Machine Learning

Abstract

AI-powered desktop assistants are reshaping the way humans interact with computers by offering voice-activated automation, intuitive task management, and smooth integration with desktop systems. The research introduces an innovative AI desktop assistant that improves upon current solutions by tackling significant issues such as sluggish response times, poor speech recognition, and an absence of comprehensive automation capabilities. Key advancements include sophisticated natural language processing (NLP) for accurate intent identification, an enhanced task execution module that facilitates efficient application launching, and clever multi-tasking features. Unlike current solutions, the proposed assistant can reliably initiate applications based on observed user behavior, thereby decreasing manual input by 40%.  Furthermore, the incorporation of reinforcement learning promotes ongoing enhancements in understanding user preferences.

This research underscores the ability of AI-powered assistants to improve productivity, streamline processes, and offer a hands-free, efficient computing experience. Future developments will aim to broaden functionalities, including cross-platform compatibility and integration with cloud-based AI services. The proposed system aim to accelerates command processing speed by 30%, achieving a response time of less than 1.2 seconds, and boosts speech recognition accuracy to 95%, surpassing traditional assistants

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References

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Published

2025-05-01

How to Cite

1.
Talakoti M, Ram AB, Jagli D, Navya Sree P, Pranitha K, Madhavi A. Transforming User Engagement Through Smart AI Desktop Assistant. J Neonatal Surg [Internet]. 2025May1 [cited 2025Sep.21];14(20S):307-1. Available from: https://jneonatalsurg.com/index.php/jns/article/view/4973

Issue

Vol. 14 No. 20S (2025): Journal of Neonatal Surgery

Section

Original Article

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