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dc.contributor.authorD'Haro, Luis Fernandoen_US
dc.contributor.authorBanchs, Rafael E.en_US
dc.contributor.authorHori, Chiorien_US
dc.contributor.authorLi, Haizhouen_US
dc.identifier.citationD'Haro, L. F., Banchs, R. E., Hori, C. & Li, H. (2018). Automatic evaluation of end-to-end dialog systems with adequacy-fluency metrics. Computer Speech and Language, 55, 200-215.
dc.description.abstractEnd-to-end dialog systems are gaining interest due to the recent advances of deep neural networks and the availability of large human–human dialog corpora. However, in spite of being of fundamental importance to systematically improve the performance of this kind of systems, automatic evaluation of the generated dialog utterances is still an unsolved problem. Indeed, most of the proposed objective metrics shown low correlation with human evaluations. In this paper, we evaluate a two-dimensional evaluation metric that is designed to operate at sentence level, which considers the syntactic and semantic information carried along the answers generated by an end-to-end dialog system with respect to a set of references. The proposed metric, when applied to outputs generated by the systems participating in track 2 of the DSTC-6 challenge, shows a higher correlation with human evaluations (up to 12.8% relative improvement at the system level) than the best of the alternative state-of-the-art automatic metrics currently available.en_US
dc.relation.ispartofComputer Speech and Languageen_US
dc.rights© 2018 Elsevier Ltd. All rights reserved.en_US
dc.subjectEngineering::Computer science and engineeringen_US
dc.titleAutomatic evaluation of end-to-end dialog systems with adequacy-fluency metricsen_US
dc.typeJournal Articleen
dc.contributor.schoolSchool of Computer Science and Engineeringen_US
dc.subject.keywordsAutomatic Evaluation Metricsen_US
dc.subject.keywordsDialog Systemsen_US
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