BoTest: a Framework to Test the Quality of Conversational Agents Using Divergent Input Examples
|Title:||BoTest: a Framework to Test the Quality of Conversational Agents Using Divergent Input Examples||Authors:||Ruane, Elayne
|Permanent link:||http://hdl.handle.net/10197/9305||Date:||11-Mar-2018||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.||Funding Details:||Science Foundation Ireland||Type of material:||Conference Publication||Publisher:||ACM||Copyright (published version):||2018 ACM||Keywords:||Conversational agent testing;Conversational agent quality assessment;Chatbot||DOI:||10.1145/3180308.3180373||Language:||en||Status of Item:||Peer reviewed||Is part of:||IUI'18 Proceedings of the 23rd International Conference on Intelligent User Interfaces Companion||Conference Details:||ACM IUI (Intelligent User Interfaces), Tokyo, Japan, 07-11 March 2018|
|Appears in Collections:||Computer Science Research Collection|
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