A data-driven approach to spoken dialog segmentation

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dc.contributor.author Griol Barres, David
dc.contributor.author Molina López, José Manuel
dc.contributor.author Sanchis de Miguel, María Araceli
dc.contributor.author Callejas Carrión, Zoraida
dc.date.accessioned 2021-11-05T11:29:04Z
dc.date.available 2022-05-28T23:00:05Z
dc.date.issued 2020-05-28
dc.identifier.bibliographicCitation Griol,D., Molina, J.M., Sanchís, A., Callejas Z. (2020). A data-driven approach to spoken dialog segmentation. Neurocomputing, 391, pp. 292-304. https://doi.org/10.1016/j.neucom.2019.02.072
dc.identifier.issn 0925-2312
dc.identifier.uri http://hdl.handle.net/10016/33543
dc.description.abstract In This Paper, We Present A Statistical Model For Spoken Dialog Segmentation That Decides The Current Phase Of The Dialog By Means Of An Automatic Classification Process. We Have Applied Our Proposal To Three Practical Conversational Systems Acting In Different Domains. The Results Of The Evaluation Show That Is Possible To Attain High Accuracy Rates In Dialog Segmentation When Using Different Sources Of Information To Represent The User Input. Our Results Indicate How The Module Proposed Can Also Improve Dialog Management By Selecting Better System Answers. The Statistical Model Developed With Human-Machine Dialog Corpora Has Been Applied In One Of Our Experiments To Human-Human Conversations And Provides A Good Baseline As Well As Insights In The Model Limitation.
dc.language.iso eng
dc.publisher Elsevier
dc.rights © 2019 Elsevier B.V. All rights reserved.
dc.rights Atribución-NoComercial-SinDerivadas 3.0 España
dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subject.other conversational interfaces
dc.subject.other dialog structure annotation
dc.subject.other domain knowledge acquisition
dc.subject.other human-machine interaction
dc.subject.other spoken interaction
dc.title A data-driven approach to spoken dialog segmentation
dc.type article
dc.subject.eciencia Informática
dc.identifier.doi https://doi.org/10.1016/j.neucom.2019.02.072
dc.rights.accessRights openAccess
dc.type.version acceptedVersion
dc.identifier.publicationfirstpage 292
dc.identifier.publicationlastpage 304
dc.identifier.publicationtitle NEUROCOMPUTING
dc.identifier.publicationvolume 391
dc.identifier.uxxi AR/0000025722
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