Data-driven strategies for an automated dialogue system (original) (raw)

2004, Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics - ACL '04

We present a prototype natural-language problem-solving application for a financial services call center, developed as part of the Amitiés multilingual human-computer dialogue project. Our automated dialogue system, based on empirical evidence from real call-center conversations, features a datadriven approach that allows for mixed system/customer initiative and spontaneous conversation. Preliminary evaluation results indicate efficient dialogues and high user satisfaction, with performance comparable to or better than that of current conversational travel information systems.