| Title | BoTest: A Framework to Test the Quality of Conversational Agents Using Divergent Input Examples |
| Publication Type | Conference Paper |
| Year of Publication | 2018 |
| Authors | Ruane, Elayne, Faure, Théo, Smith, Ross, Bean, Dan, Carson-Berndsen, Julie, Ventresque, Anthony |
| Conference Name | Proceedings of the 23rd International Conference on Intelligent User Interfaces Companion |
| Publisher | ACM |
| Conference Location | New York, NY, USA |
| ISBN Number | 978-1-4503-5571-1 |
| Keywords | chatbot, conversation agents, conversational agent, Conversational Agent Quality Assessment, Conversational Agent Testing, Human Behavior, Metrics, pubcrawl, Scalability |
| Abstract | Quality of conversational agents is important as users have high expectations. Consequently, poor interactions may lead to the user abandoning the system. In this paper, we propose a framework to test the quality of conversational agents. Our solution transforms working input that the conversational agent accurately recognises to generate divergent input examples that introduce complexity and stress the agent. As the divergent inputs are based on known utterances for which we have the 'normal' outputs, we can assess how robust the conversational agent is to variations in the input. To demonstrate our framework we built ChitChatBot, a simple conversational agent capable of making casual conversation. |
| URL | http://doi.acm.org/10.1145/3180308.3180373 |
| DOI | 10.1145/3180308.3180373 |
| Citation Key | ruane_botest:_2018 |
BoTest: A Framework to Test the Quality of Conversational Agents Using Divergent Input Examples