The Amitiés system: Data-driven techniques for automated dialogue
| Autor: | Min Wu, Alan W. Biermann, R. Bryce Inouye, Tomek Strzalkowski, Hilda Hardy, Cristian Ursu, Nick Webb, Ashley McKenzie |
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| Rok vydání: | 2006 |
| Předmět: |
Linguistics and Language
business.industry Computer science Communication media_common.quotation_subject Frame (networking) computer.software_genre Language and Linguistics Computer Science Applications Identification (information) Telephone banking Modeling and Simulation Information system Conversation Multilingualism Computer Vision and Pattern Recognition Artificial intelligence business computer Software Natural language processing Natural language Spoken language media_common |
| Zdroj: | Speech Communication. 48:354-373 |
| ISSN: | 0167-6393 |
| Popis: | We present a natural-language customer service application for a telephone banking call center, developed as part of the AMITIES dialogue project (Automated Multilingual Interaction with Information and Services). Our dialogue system, based on empirical data gathered from real call-center conversations, features data-driven techniques that allow for spoken language understanding despite speech recognition errors, as well as mixed system/customer initiative and spontaneous conversation. These techniques include robust named-entity extraction, slot-filling Frame Agents, vector-based task identification and dialogue act classification, a Bayesian database record selection algorithm, and a natural language generator designed with templates created from real agents' expressions. Preliminary evaluation results indicate efficient dialogues and high user satisfaction, with performance comparable to or better than that of current conversational information systems. |
| Databáze: | OpenAIRE |
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