Intelligent Student Support System Using Multilingual Conversational AI
Prof. Tanaya Bala Behera1, Chandrakanth2, Chetan3, Chinnirathod Gandhikumar4, Darshan B5
1st Prof. Tanaya Bala Behera
dept. Computer Science &Engineering
Dayananda Sagar University Bengaluru, India
tanya-cse@dsu.edu.in
2nd Chandrakanth
dept. Computer Science & Engineering
Dayananda Sagar University
Bengaluru, India chandrakantgovindingle@gmail.com
3rd Chetan
dept. Computer Science & Engineering
Dayananda Sagar University Bengaluru, India chetanghorwade@gmail.com
4th Chetan
dept. Computer Science & Engineering
Dayananda Sagar University
Bengaluru, India
gandhikumarrathod@gmail.com
5th Darshan B
dept. Computer Science & Engineering
Dayananda Sagar University
Bengaluru, India
darshandarshanbb1@gmail.com
Abstract - In general, in most colleges, students and their parents face difficulty in getting proper information regarding admission, exams, fees, placement, etc. Though most of the colleges are providing the information in their website, it is quite time-consuming to search for the particular information. In order to overcome this difficulty, the present project proposes the development of an “Intelligent Student Support System Using a Multilingual Conversational Chatbot.” This system will help to provide instant responses to the queries of the students in an automated way. The chatbot is created using Python programming with the help of the Flask framework. Natural Language Processing techniques are used to understand the queries of the students. According to the intent of the query, the system will fetch the information from the structured knowledge base and will respond appropriately to the students. Although the chatbot is currently designed to accept only text-based queries, it is possible to add voice-based queries in the near future to increase the accessibility of the system. In addition, the queries are kept in the database to further improve the system in the future. The solution provided here reduces the workload of the administration staff, saves time for the end-users, and also helps in better communication between the students and the institution. Thus, the system provided here is a simple, efficient, and effective way to automate the college enquiry system.
Key Words: Artificial Intelligence, Natural Language Processing (NLP), Chatbot, College Enquiry System, Multilingual Support, Conversational AI, Flask Framework, Machine Learning
