Published on 01 January 2018

Syncing up for a good conversation: Objective acoustic-prosodic measures and expert clinical assessment of conversational entrainment

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Borrie, Stephanie A.;Barrett, Tyson S.;Willi, Megan;Berisha, Visar

Description

Purpose: Conversational entrainment, thephenomenon whereby communication partners align their behavior with one another,is considered essential for productive and fulfilling conversation. Lackof entrainment could, therefore, impact conversational success. While studiedin many disciplines, entrainment has received limited attention in the field ofspeech-language pathology, where its implications may have direct clinicalrelevance. Here, we couple objective measures of speech signal entrainment andexpert clinical assessment to characterize conversational entrainment within amultidimensional, clinically-meaningful framework.Method:Using anovel computational approach to quantify acoustic-prosodic entrainment, and real-world evidenceof conversational success, as judged by five speech-language pathologists, we investigated conversationalentrainment across multiple speech dimensions in a corpus of 57 experimentally-elicited conversations involvinghealthy subjects. Results: Expert clinical assessment of conversation is supportedby objective measures of entrainment in rhythmic, articulatory and phonatory dimensionsof speech. Approach validation is achieved by comparing outputmeasures from real versus sham conversations; and prediction accuracy of entrainedversus non-entrained measure models. Conclusions: A methodology forcapturing conversational entrainment, validated in healthy populations, has importanttranslational application for disciplines such asspeech-language pathology where conversational entrainment represents acritical knowledge gap in the field, as well as a potential target for remediation.

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Metrics

Dataset Index

1.7

FAIR Score

69%

Citations

0

Mentions

0

Metrics Over Time

Publication Details

DOI

Publisher

ICPSR - Interuniversity Consortium for Political and Social Research

Assigned Domain

Subfield

Language and Linguistics

Field

Arts and Humanities

Domain

Social Sciences

Confidence Score

50%

Source

Scholar Data Model

Normalization Factors

FT

13.46

CTw

1.00

MTw

1.00