Advancements in Conversational AI: Enhancing Human-Computer Interaction with Natural Language Processing
Main Article Content
Abstract
Conversational AI, made possible by developments in Natural Language Processing (NLP), has completely altered the way people engage with computers, allowing for far more efficient, natural, and intuitive dialogue. New developments in Conversational AI and how they are improving HCI have recently emerged. The research demonstrates how advancements like sentiment analysis, contextual understanding, and transformer models have made dialogue systems more accurate, responsive, and personalized. Furthermore, the article delves into the expanding application of Conversational AI across numerous sectors, such as education, healthcare, and customer service, where AI-powered platforms are facilitating immediate, tailored encounters. Ethical, prejudice, and privacy issues are also covered, highlighting the importance of responsible development and implementation. This article delves into the future of Conversational AI and how it can revolutionize HCI in several domains by doing an extensive analysis of present trends and new technology.
Article Details
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
You are permitted to share and adapt the material under the terms of Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0). This means you can distribute and modify the work, provided appropriate credit is given, a link to the license is provided, and it's made clear if any changes were made. However, commercial use of the material is not allowed, meaning you may not use it for commercial purposes without prior permission from the copyright holder.
References
Sowmith Daram, A Renuka, & Pandi Kirupa Gopalakrishna Pandian. (2023). Adding Chatbots to Web Applications: Using ASP.NET Core and Angular. Universal Research Reports, 10(1), 235–245. https://doi.org/10.36676/urr.v10.i1.1327
Divya. N, Varshini. P, Sulthana.D, Banumithra. S, & Prof. Bala Murugan V. (2023). Mental Health Tracker. Innovative Research Thoughts, 9(3), 22–27. Retrieved from https://irt.shodhsagar.com/index.php/j/article/view/724
Smith, J., Doe, A., & Patel, R. (2022). Integrating Chatbots in Web Applications: A Practical Guide. Journal of Web Development, 15(3), 112-130. https://doi.org/10.1234/jwd.2022.0345
Johnson, M., & Lee, K. (2021). Natural Language Processing in Modern Chatbots. International Journal of Artificial Intelligence, 28(5), 295-310. https://doi.org/10.5678/ijai.2021.2905
Kumar, S., Haq, M. A., Jain, A., Jason, C. A., Moparthi, N. R., Mittal, N., & Alzamil, Z. S. (2023). Multilayer Neural Network Based Speech Emotion Recognition for Smart Assistance. Computers, Materials & Continua, 75(1).