  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.
