Interaction quality estimation using long short-term memories

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• dc.contributor.author Rach, Niklasca
• dc.contributor.author Minker, Wolfgangca
• dc.contributor.author Ultes, Stefanca
• dc.date.accessioned 2017-12-18T16:05:57Z
• dc.date.available 2017-12-18T16:05:57Z
• dc.date.issued 2017
• dc.description Comunicació presentada a SIGDIAL 2017 Conference, the 18th Annual Meeting of the Special Interest Group on Discourse and Dialogue, celebrada del 15 al 17 d'agost a Saarbrucken, Alemanya.ca
• dc.description.abstract For estimating the Interaction Quality (IQ) in Spoken Dialogue Systems (SDS), the dialogue history is of significant importance. Previous works included this information manually in the form of precomputed temporal features into the classification process. Here, we employ a deep learning architecture based on Long Short-Term Memories (LSTM) to extract this information automatically from the data, thus estimating IQ solely by using current exchange features. We show that it is thereby possible to achieve competitive results as in a scenario where manually optimized temporal features have been included.en
• dc.description.sponsorship This work is part of a project that has received funding from the European Unions Horizon 2020 research and innovation programme under grant agreement No 645012.en
• dc.format.mimetype application/pdfca
• dc.identifier.citation Rach N, Minker W, Ultes S. Interaction quality estimation using long short-term memories. In: Proceedings of the SIGDIAL 2017 Conference. 18th Annual Meeting of the Special Interest Group on Discourse and Dialogue; 2017 Aug 15-17; Saarbrucken, Germany. Saarbrucken: ACL, 2017. p. 164-9.
• dc.identifier.isbn 978-1-945626-82-1
• dc.identifier.uri http://hdl.handle.net/10230/33525
• dc.language.iso eng
• dc.publisher ACL (Association for Computational Linguistics)ca
• dc.relation.ispartof Proceedings of the SIGDIAL 2017 Conference. 18th Annual Meeting of the Special Interest Group on Discourse and Dialogue; 2017 Aug 15-17; Saarbrucken, Germany. Saarbrucken: ACL, 2017. p. 164-9.
• dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/645012
• dc.rights © ACL, Creative Commons Attribution 4.0 License
• dc.rights.accessRights info:eu-repo/semantics/openAccess
• dc.rights.uri http://creativecommons.org/licenses/by/4.0/
• dc.subject.keyword Spoken dialogue systemen
• dc.subject.keyword Quality estimationen
• dc.subject.keyword long short-term memoriesen
• dc.subject.keyword LSTM
• dc.title Interaction quality estimation using long short-term memoriesca
• dc.type info:eu-repo/semantics/conferenceObject
• dc.type.version info:eu-repo/semantics/publishedVersion