Paper: Data-Driven Strategies For An Automated Dialogue System

ACL ID P04-1010
Title Data-Driven Strategies For An Automated Dialogue System
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2004
Authors

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 data- driven 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.