Ong Sing Goh

2papers

2 Papers

AIJan 26, 2016
Intelligent Conversational Bot for Massive Online Open Courses (MOOCs)

Ser Ling Lim, Ong Sing Goh

Massive Online Open Courses (MOOCs) which were introduced in 2008 has since drawn attention around the world for both its advantages as well as criticism on its drawbacks. One of the issues in MOOCs which is the lack of interactivity with the instructor has brought conversational bot into the picture to fill in this gap. In this study, a prototype of MOOCs conversational bot, MOOC-bot is being developed and integrated into MOOCs website to respond to the learner inquiries using text or speech input. MOOC-bot is using the popular Artificial Intelligence Markup Language (AIML) to develop its knowledge base, leverage from AIML capability to deliver appropriate responses and can be quickly adapted to new knowledge domains. The system architecture of MOOC-bot consists of knowledge base along with AIML interpreter, chat interface, MOOCs website and Web Speech API to provide speech recognition and speech synthesis capability. The initial MOOC-bot prototype has the general knowledge from the past Loebner Prize winner - ALICE, frequent asked questions, and a content offered by Universiti Teknikal Malaysia Melaka (UTeM). The evaluation of MOOC-bot based on the past competition questions from Chatterbox Challenge (CBC) and Loebner Prize has shown that it was able to provide correct answers most of the time during the test and demonstrated the capability to prolong the conversation. The advantages of MOOC-bot such as able to provide 24-hour service that can serve different time zones, able to have knowledge in multiple domains, and can be shared by multiple sites simultaneously have outweighed its existing limitations.

RONov 5, 2014
An Intelligent Personal Robot Assistant

Ong Sing Goh, Lance Fung

Recent development in developing humanoid robot poses new challenges to human-machine interaction communication. A major challenge is to develop robots that can behave like and interact with human in the most natural way possible. This paper proposes a system to develop a robot that can receive command, and talk to people in natural language. In addition, the robot can also be "trained" to become an expert in sepcific areas to provide expert advice to human-beings. Most important of all, the robot can display emotions through facial expression, speech and gesture so that the interaction process will become more comprehensive and compelling.