ALICE Pattern Matching Based Chatbot for Natural Language Communication: System Development and Testing

Abstract

The simulation of human processes using Artificial Intelligence (AI) features is finding place in various fields including the e-learning environment. Chatbot system using text and voice, recognizing images, analyzing the sentiments, and generating natural language is latest utility based on AI concepts. The chatbot systems are becoming more common due to their benefits as a support mechanism helping human beings in their day to day tasks. This project aimed at developing and testing a chatbot system to communicate with the education sector users using natural language through android based application creating a smart education environment. The project developed an online chatting platform using Artificial Linguistic Internet Computer Entity (ALICE) Pattern Matching techniques where students could communicate related to their learning activities such as submission deadline of the reports and assignments, student’s information, co-curricular and extracurricular activities. The system design uses a Raspberry Pi 3 which works as Transmission Control Protocol (TCP) server and uses three different types of pattern matching techniques which are keyword detection, symbolic reduction, and synonyms resolution. An android user interface application is also designed which works as TCP client. The system design uses a database for student information system in the Python server.  The obtained results are in voice and text format from the android user interface application and are displayed on Python Interpreter. The developed project system can enhance the student engagement in learning activities. This system can also help teachers in saving their time and to support them to utilize their class timings for other co-curricular activities like synchronous and asynchronous activities to support active learning and flipped learning. The proposed system has the potential to test and analyze various factors as use of technology, student learning including impact of student engagements in their learning activities.