Abstract
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.
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CITATION STYLE
Hardy, H., Strzalkowski, T., Wu, M., Ursu, C., Webb, N., Biermann, A., … McKenzie, A. (2004). Data-driven strategies for an automated dialogue system. In Proceedings of the Annual Meeting of the Association for Computational Linguistics (pp. 71–78). Association for Computational Linguistics (ACL). https://doi.org/10.3115/1218955.1218965
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