Measuring Prosodic Entrainment in Conversation: A Review and Comparison of Different Methods.
Purpose: This study aims to further our understanding of prosodic entrainment and its different subtypes by analyzing a single corpus of conversations with 12 different methods and comparing the subsequent results. Method: Entrainment on three fundamental frequency features was analyzed in a subset...
| Published in: | Journal of Speech, Language & Hearing Research Vol. 66; no. 11; pp. 4280 - 4315 |
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| Main Authors: | , , , |
| Format: | Article |
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American Speech-Language-Hearing Association
Nov2023
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| Subjects: | |
| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=173573522&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 173573522 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 10924388 1SM jtl: Journal of Speech, Language & Hearing Research issn: 10924388 maglogo: N pubinfo: dt: Nov2023 vid: 66 iid: 11 pid: 42 pub: American Speech-Language-Hearing Association artinfo: ui: 173573522 10.1044/2023_JSLHR-23-00094 ppf: 4280 ppct: 35 formats: fmt: @attributes: type: P size: 1.9MB tig: atl: Measuring Prosodic Entrainment in Conversation: A Review and Comparison of Different Methods. aug: au: Kruyt, Joanna de Jong, Dorina D’Ausilio, Alessandro Beňuš, Štefan affil: Institute of Informatics, Slovak Academy of Sciences, Bratislava, Slovakia. Faculty of Informatics and Information Technologies, Slovak Technical University, Bratislava, Slovakia. Istituto Italiano di Tecnologia, Center for Translational Neurophysiology of Speech and Communication, Ferrara, Italy. Università di Ferrara, Dipartimento di Neuroscienze. Riabilitazione, Italy e Constantine the Philosopher University, Nitra, Slovakia. su: Conversation Speech Time Regression analysis sug: subj: Conversation Speech Time Regression analysis ab: Purpose: This study aims to further our understanding of prosodic entrainment and its different subtypes by analyzing a single corpus of conversations with 12 different methods and comparing the subsequent results. Method: Entrainment on three fundamental frequency features was analyzed in a subset of recordings from the LUCID corpus (Baker & Hazan, 2011) using the following methods: global proximity, global convergence, local proximity, local convergence, local synchrony (Levitan & Hirschberg, 2011), prediction using linear mixed-effects models (Schweitzer & Lewandowski, 2013), geometric approach (Lehnert-LeHouillier, Terrazas, & Sandoval, 2020), time-aligned moving average (Kousidis et al., 2008), HYBRID method (De Looze et al., 2014), crossrecurrence quantification analysis (e.g., Fusaroli & Tylén, 2016), and windowed, lagged cross-correlation (Boker et al., 2002). We employed entrainment measures on a local timescale (i.e., on adjacent utterances), a global timescale (i.e., over larger time frames), and a time series–based timescale that is larger than adjacent utterances but smaller than entire conversations. Results: We observed variance in results of different methods. Conclusions: Results suggest that each method may measure a slightly different type of entrainment. The complex implications this has for existing and future research are discussed. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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