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Voice Recognition System with STORJ Decentralized Storage

9 pagesPublished: August 6, 2024

Abstract

The proposed Virtual Assistant System (VAS) represents a new solution revolutionizing user interactions with technology by seamlessly integrating Natural Language Processing (NLP) and Artificial Intelligence (AI), facilitating effortless communication through voice commands. By employing cutting-edge speech recognition algorithms, the proposed system accurately translates the voice input into text, adapting responses based on individual user preferences over time. The proposed system offers a diverse range of functionalities including information retrieval, task automation, and smart home control to assist users in managing the tasks hands-free with an intelligent interface providing varying levels of technical expertise. Safeguarding user privacy and control, the system allows users to opt-in or opt-out of data collection with complete transparency and robust security measures. Continuous improvement through extensive testing and user feedback addresses the challenges like accurately interpreting complex commands, positioning the Virtual Assistant System (VAS) as a sophisticated, personalized, and privacy-aware solution at the forefront of virtual assistant technology.

Keyphrases: artificial intelligence (ai), automation, data analysis, smart home, user privacy, virtual assistance

In: Rajakumar G (editor). Proceedings of 6th International Conference on Smart Systems and Inventive Technology, vol 19, pages 73-81.

BibTeX entry
@inproceedings{ICSSIT2024:Voice_Recognition_System_with,
  author    = {S.L. Jany Shabu and R A Pooja and J Ronie Joe and J Refonaa and S Praveen and R Abirami},
  title     = {Voice Recognition System with STORJ Decentralized Storage},
  booktitle = {Proceedings of 6th International Conference on Smart Systems and Inventive Technology},
  editor    = {Rajakumar G},
  series    = {Kalpa Publications in Computing},
  volume    = {19},
  publisher = {EasyChair},
  bibsource = {EasyChair, https://easychair.org},
  issn      = {2515-1762},
  url       = {/publications/paper/5784},
  doi       = {10.29007/cdbc},
  pages     = {73-81},
  year      = {2024}}
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