Measuring and implementing lexical alignment: A systematic literature review

dc.contributor.affiliationUniversidade de Santiago de Compostela. Departamento de Electrónica e Computación
dc.contributor.affiliationUniversidade de Santiago de Compostela. Centro de Investigación en Tecnoloxías Intelixentes da USC (CiTIUS)
dc.contributor.authorSrivastava, Sumit
dc.contributor.authorWentzel, Suzanna D.
dc.contributor.authorCatalá Bolós, Alejandro
dc.contributor.authorTheune, Mariët
dc.date.accessioned2025-04-16T08:44:06Z
dc.date.available2025-04-16T08:44:06Z
dc.date.issued2025-03
dc.description.abstractLexical Alignment is a phenomenon often found in human–human conversations, where the interlocutors converge during a conversation to use the same terms and phrases for the same underlying concepts. Alignment (linguistic) is a mechanism used by humans for better communication between interlocutors at various levels of linguistic knowledge and features, and one of them is lexical. The existing literature suggests that alignment has a significant role in communication between humans, and is also beneficial in human–agent communication. Various methods have been proposed in the past to measure lexical alignment in human–human conversations, and also to implement them in conversational agents. In this research, we carry out an analysis of the existing methods to measure lexical alignment and also dissect methods to implement it in a conversational agent for personalizing human–agent interactions. We propose a new set of criteria that such methods should meet and discuss the possible improvements that can be made to existing methods.
dc.description.peerreviewedSI
dc.description.sponsorshipContribution from the ITN project NL4XAI (Natural Language for Explainable AI ). This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 860621. This document reflects the views of the author(s) and does not necessarily reflect the views or policy of the European commission. The REA cannot be held responsible for any use that may be made of the information this document contains. This work was par- tially supported under grants PID2021-123152OB-C21 and TED2021-130295B-C33 funded by MCIN/AEI/10.13039/501100011033 and the Xunta de Galicia - Consellería de Cultura, Educación, Formación Profesional e Universidades (grants ED431F2018/02, ED431G2019/04, ED431C2022/19), co-funded by the European Regional Development Fund (ERDF/FEDER program)
dc.identifier.citationSrivastava, S., Wentzel, S.D., Catalá Bolós, A., Theune, M. (2025). Measuring and implementing lexical alignment: A systematic literature review. "Computer Speech & Language", vol. 90
dc.identifier.doi10.1016/j.csl.2024.101731
dc.identifier.essn0885-2308
dc.identifier.urihttps://hdl.handle.net/10347/40844
dc.journal.titleComputer Speech & Language
dc.language.isoeng
dc.publisherElsevier
dc.relation.projectIDinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2019-109400RB-I00/ES/ENSAYO CLINICO ALEATORIZADO PARA LA EVALUACION DE LA EFICACIA DE UN TRATAMIENTO PSICOLOGICO PARA DEJAR DE FUMAR CON EL APOYO DE UNA APP/
dc.relation.projectIDinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023/PID2021-123152OB-C21/ES/INTELIGENCIA ARTIFICIAL EXPLICABLE PARA EL ENVEJECIMIENTO SALUDABLE/
dc.relation.publisherversionhttps://dx.doi.org/10.1016/j.csl.2024.101731
dc.rights© 2024 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license
dc.rightsAttribution 4.0 Internationalen
dc.rights.accessRightsopen access
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectLexical alignment
dc.subjectEntrainment
dc.subjectMeasurement
dc.subjectConversational agents
dc.subject.classification3307 Tecnología electrónica
dc.titleMeasuring and implementing lexical alignment: A systematic literature review
dc.typejournal article
dc.type.hasVersionVoR
dc.volume.number90
dspace.entity.typePublication
relation.isAuthorOfPublication2d82830a-9264-499e-905a-dba76d3676fc
relation.isAuthorOfPublication.latestForDiscovery2d82830a-9264-499e-905a-dba76d3676fc

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