Document Type
Conference Paper
Publication Date
12-20-2019
Keywords
human-computer interaction, artificial intelligence (AI), computation and language, information retrieval, chatbots, IBM Watson, language translator, speech to text, text to speech, tone analyzer
Abstract
Systems powered by artificial intelligence are being developed to be more user-friendly by communicating with users in a progressively human-like conversational way. Chatbots, also known as dialogue systems, interactive conversational agents, or virtual agents are an example of such systems used in a wide variety of applications ranging from customer support in the business domain to companionship in the healthcare sector. It is becoming increasingly important to develop chatbots that can best respond to the personalized needs of their users so that they can be as helpful to the user as possible in a real human way. This paper investigates and compares three popular existing chatbots API offerings and then propose and develop a voice interactive and multilingual chatbot that can effectively respond to users mood, tone, and language using IBM Watson Assistant, Tone Analyzer, and Language Translator. The chatbot was evaluated using a use case that was targeted at responding to users needs regarding exam stress based on university students survey data generated using Google Forms. The results of measuring the chatbot effectiveness at analyzing responses regarding exam stress indicate that the chatbot responding appropriately to the user queries regarding how they are feeling about exams 76.5%. The chatbot could also be adapted for use in other application areas such as student info-centers, government kiosks, and mental health support systems.
Faculty
Sheridan Research
Version
Pre-print
Copyright
© Kennedy Ralston, Yuhao Chen, Haruna Isah, & Farhana Zulkernine, 2019
Terms of Use
Terms of Use for Works posted in SOURCE.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Original Publication Citation
Ralston, R., Chen, Y., Isah, H., and Zulkernine, F. (2019). A Voice Interactive Multilingual Student Support System using IBM Watson. arXiv. https://doi.org/10.48550/arXiv.2001.00471
SOURCE Citation
Ralston, Kennedy; Chen, Yuhao; Isah, Haruna; and Zulkernine, Farhana, "A Voice Interactive Multilingual Student Support System using IBM Watson" (2019). Publications and Scholarship. 9.
https://source.sheridancollege.ca/centres_publications/9
Included in
Academic Advising Commons, Artificial Intelligence and Robotics Commons, Educational Technology Commons, Higher Education Commons
Comments
Delivered at the Eighteenth International Conference on Machine Learning and Applications (ICMLA 2019) in Boca Raton, Florida, December 16-19, 2019.