Aug 2026· International Conference Computational Vision and Bio Inspired Computing· pp. 849-855· 0 citations· 16 references
Abstract
This proposed system centers around the creation of an AI-based FAQ Chatbot with Voice Assist. This Chatbot allows users to interact with the service using natural voice commands. In the conventional approach, the FAQ section is handled by the support staff, but this system automates the entire process using Artificial Intelligence. Using a browser, the chatbot collects the user's voice data, transcribes the audio using speech recognition, and applies NLP techniques like TF-IDF and cosine similarity to retrieve the most relevant answer from the stored FAQ data. If there is a lack of confidence in answering the question, the input is stored as an unknown answer for administration review and the user input is captured as unanswered questions. These questions can then be reviewed by admins and appropriate responses provided which will allow the admin to refine the stored responses, thus enhancing the system's intelligence. Furthermore, the responses are delivered through text-to-speech outputs which allow users to listen to the answers. By integrating voice commands, responsive intelligent interface, and the admin feedback loop, the system's capability to enhance user experiences and refine self-responding systems through continuous improvement is extraordinary. The proposed system was tested with 496 test queries, comprising of original and rephrased FAQ queries, and the accuracy of response was found to be 97.58% with an average retrieval time of 0.0018 seconds.
Higher education organizations face a huge number of repetitive inquiries from students regarding admissions, fee payments, exams, scholarships, placements, and other campus-related aspects. Inquiries are made in various languages, resulting in communication difficulties and increased work pressure on the administrativ...
Abhijit Shankar Jadhav, Gajul N. B.· Recent Research Reviews Jour...· 0 citations
Artificial intelligence (AI) chatbots powered by natural language processing (NLP) have transformed human-computer interaction across sectors such as e-commerce, healthcare, and customer service. This paper reviews the evolution of chatbot technology, with a particular focus on the components that constitute modern sys...
S. Nalawade, H. Tapase, Shreya Jadhav· Journal of Big Data Technolo...· 0 citations
The experimental results obtained were 92% response accuracy, 90% retrieval relevance, 1.8 s response time on average, and 91% user satisfaction, thus proving the efficiency of the suggested architecture in providing reliable and scalable academic information services.
Arun Babu P., P. Sree, Lingala Anusha et al.· Journal of Information Techn...· 0 citations
This project presents an AI-Powered College Enquiry Chatbot that automates common college-related queries using Retrieval-Augmented Generation (RAG) and provides an administrative dashboard for managing FAQ content and monitoring chatbot performance.
G. Vamsi, N. Charan· International Journal for Re...· 0 citations
The results show that the RAG architecture provides a scalable alternative for creating precise, contextually grounded conversational agents, thereby mitigating some of the main drawbacks of LLMs.
Rabia Shabbir, K. Talpur, Shakeel Ahmad· ICCK Transactions on Machine...· 0 citations
Many voice interaction applications require exact control over both the content and delivery of responses, typically using pre-recorded lines. Recent full-duplex models respond with low latency but cannot guarantee exact content or reproduce a specific recorded performance, while cascaded systems can be constrained to...
Sathvik Udupa, Naveen Kumar, Ryan Folmsbee· 0 citations
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