Artificially Intelligent Response Based Utility Management System
Rakshata P1, Padma H V2, Meghana Prakash3, and Karthik V4
1Rakshata P, Department of Computer Science and Engineering, Vidyavardhaka College of Engineering, Mysuru, (Karnataka), India.
2Padma H V, Department of Computer Science and Engineering, Vidyavardhaka College of Engineering, Mysuru, Karnataka, India.
3Meghana Prakash, Department of Computer Science and Engineering, Vidyavardhaka College of Engineering, Mysuru, (Karnataka), India.
4Karthik V, Department of Computer Science and Engineering, Vidyavardhaka College of Engineering, Mysuru, (Karnataka), India.
Manuscript received on 13 March 2019 | Revised Manuscript received on 19 March 2019 | Manuscript published on 30 July 2019 | PP: 5038-5040 | Volume-8 Issue-2, July 2019 | Retrieval Number: B1085078219/19©BEIESP | DOI: 10.35940/ijrte.B1085.078219
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Every organization should have its very own Personal AI Assistant at its disposal. The aim of the assistant is to find a knowledge gap to fill by its well-structured speech synthesis and generation mechanisms. The inquiry or interrogation can be predominantly generic to the requirements of the institution. The assistant will understand based on the clarity of purpose. Responses are original, innovative, clear and concise as its vital to provide correct up to date information. They can also be visual and graphical based on the question. Extracted data from private data sets of the organization are analyzed and organized using Pandas. Speech Recognition, Understanding, and Synthesis are done using Speech Recognition Packages and Natural Language Processing Techniques.
Index Terms: Artificial Intelligent, Personal Assistant, Natural Language Processing, Speech Recognition
Scope of the Article: Artificial Intelligent Methods, Models, Techniques