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Báo cáo khoa học: "Data-Driven Strategies for an Automated Dialogue System"
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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. . | Data-Driven Strategies for an Automated Dialogue System Hilda HARDY Tomek STRZALKOWSKI Min WU ILS Institute University at Albany SUNY 1400 Washington Ave. SS262 Albany nY 12222 USA hhardy tomek minwu@ cs.albany.edu Cristian URSU Nick WEBB Department of Computer Science University of Sheffield Regent Court 211 Portobello St. Sheffield S1 4DP UK c.ursu@sheffield. ac.uk n.webb@dcs.shef.ac.uk Alan BIERMANN R. Bryce INOUYE Ashley MCKENZIE Department of Computer Science Duke University P.O. Box 90129 Levine Science Research Center D101 Durham NC 27708 USA awb rbi armckenz@cs.duke.edu 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. 1 Introduction Recently there has been a great deal of interest in improving natural-language human-computer conversation. Automatic speech recognition continues to improve and dialogue management techniques have progressed beyond menu-driven prompts and restricted customer responses. Yet few researchers have made use of a large body of human-human telephone calls on which to form the basis of a data-driven automated system. The Amitiés project seeks to develop novel technologies for building empirically induced dialogue processors to support multilingual human-computer interaction and to integrate these technologies into systems for accessing information and services http www.dcs.shef.ac. uk nlp amities . Sponsored jointly by the European Commission and the US Defense Advanced Research Projects Agency the .