Conversational AI: A Comprehensive Study on Building and Enhancing Chatbot Systems

Authors

  • Hemendra Kumar Jain, Kotla Veera Venkata Satya Sai Narayana, Shaik Asad Ashraf, Pendyala Venkat Subash, S. Sri Harsha

Keywords:

Conversational AI, Chatbot Systems, Natural Language Processing, Ethical AI, Real-world Applications, Model Optimization

Abstract

Conversational AI has become a game-changing technology with a wide range of uses, from customer service systems to virtual assistants. With the goal of offering a thorough grasp of the area and advancing it, this research provides an extensive analysis on the creation and improvement of Conversational AI. The paper starts with a history of conversational AI, outlining its development and significant events. A comprehensive analysis of the literature delves into the latest technology, frameworks, and obstacles encountered by current chatbot systems. The study takes a hands-on approach, outlining the model architecture, training, and data gathering procedures. The Conversational AI model that has been constructed performs well, making use of cutting-edge natural language processing methods. Its effectiveness in real-world circumstances is demonstrated by experimental findings, which significantly outperform current standards. We talk about the architecture of the model, highlighting its advantages and possible areas for improvement. Successful implementations of Conversational AI in a variety of contexts, including as customer service and education, are demonstrated by real-world case studies. To guarantee responsible deployment, ethical factors like bias mitigation and user privacy are considered.

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Published

24.03.2024

How to Cite

Kotla Veera Venkata Satya Sai Narayana, Shaik Asad Ashraf, Pendyala Venkat Subash, S. Sri Harsha , H. K. J. . . . . . (2024). Conversational AI: A Comprehensive Study on Building and Enhancing Chatbot Systems. International Journal of Intelligent Systems and Applications in Engineering, 12(3), 2431–2437. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/5714

Issue

Vol. 12 No. 3 (2024)

Section

Research Article

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