Classifying conversational entrainment of speech behavior: An expanded framework and review

Wynn, Camille J.; Borrie, Stephanie A.

doi:10.1016/j.wocn.2022.101173

Cited by 15 publications

(8 citation statements)

References 73 publications

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“…We thus expect that human-like gaze behavior by a robot during HRI would also have a positive influence on the entrainment exhibited by human interlocutors. Although the original study [35] examining only a single feature of the mean pitch did not find support for this expectation, entrainment has been established as a complex and multi-faceted phenomenon [18,50]. Therefore, we believe that employing comprehensive features and extensive analysis could shed additional light on the relationship between speech entrainment and gaze behavior.…”

Section: Hypothesismentioning

confidence: 88%

“…According to the psycholinguistic literature, entrainment happens on various linguistic dimensions, such as acoustic-prosodic features [13], lexical choice [14], syntactic structure [15], or semantic [16,17]. A comprehensive discussion on the types of entrainment, classification criteria, and terminology can be found in [18]. All these approaches assess the level of similarity of different linguistic features and attribute the similarities to internal (social)cognitive mechanisms or external social factors.…”

Section: Introductionmentioning

confidence: 99%

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Does a Robot’s Gaze Behavior Affect Entrainment in HRI?

Kejriwal,

Mishra,

Offrede

et al. 2024

Preprint

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Speakers tend to engage in adaptive behavior, known as entrainment, when they reuse their partner's linguistic representations, including lexical, acoustic-prosodic, semantic, or syntactic structures, during a conversation. Studies have explored the relationship between entrainment and social factors such as likeability, task success, and rapport. Still, limited research has investigated the relationship between entrainment and gaze. To address this gap, we conducted a within-subjects user study (N = 33) to test if gaze behavior of a robotic head affects entrainment of subjects toward the robot on four linguistic dimensions: lexical, syntactic, semantic, and acoustic-prosodic. Our results show that participants entrain more on lexical and acoustic-prosodic features when the robot exhibits well-timed gaze aversions similar to the ones observed in human gaze behavior, as compared to when the robot keeps staring at participants constantly. Our results support the predictions of computers are social actors (CASA) model and suggest that implementing well-timed gaze aversion behavior in a robot can lead to speech entrainment in human-robot interactions.

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Section: Hypothesismentioning

confidence: 88%

Section: Introductionmentioning

confidence: 99%

Does a Robot’s Gaze Behavior Affect Entrainment in HRI?

Kejriwal,

Mishra,

Offrede

et al. 2024

Preprint

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“…Entrainment is defined as the repetition of structures, for instance, lexical and syntactic structures between interlocutors in a conversation, but it also includes prosodic, acoustic, and visual aspects such as body posture, facial expression, and accent (Chartrand & Bargh, 1999; Chartrand & Lakin, 2013; Duran, Paxton, & Fusaroli, 2019; Healey et al., 2014; Louwerse, Dale, Bard, & Jeuniaux, 2012; Ostrand & Chodroff, 2021; Pickering & Garrod, 2004; Rasenberg et al., 2020, 2020; Scheflen, 1964; Shockley, Santana, & Fowler, 2003; Wynn & Borrie, 2022). While acknowledging the importance of all these aspects, we focus here on verbal entrainment as a starting point.…”

Section: Introductionmentioning

confidence: 99%

Language‐Specific Constraints on Conversation: Evidence from Danish and Norwegian

Dideriksen,

Christiansen,

Dingemanse

et al. 2023

Cognitive Science

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Establishing and maintaining mutual understanding in everyday conversations is crucial. To do so, people employ a variety of conversational devices, such as backchannels, repair, and linguistic entrainment. Here, we explore whether the use of conversational devices might be influenced by cross‐linguistic differences in the speakers’ native language, comparing two matched languages—Danish and Norwegian—differing primarily in their sound structure, with Danish being more opaque, that is, less acoustically distinguished. Across systematically manipulated conversational contexts, we find that processes supporting mutual understanding in conversations vary with external constraints: across different contexts and, crucially, across languages. In accord with our predictions, linguistic entrainment was overall higher in Danish than in Norwegian, while backchannels and repairs presented a more nuanced pattern. These findings are compatible with the hypothesis that native speakers of Danish may compensate for its opaque sound structure by adopting a top‐down strategy of building more conversational redundancy through entrainment, which also might reduce the need for repairs. These results suggest that linguistic differences might be met by systematic changes in language processing and use. This paves the way for further cross‐linguistic investigations and critical assessment of the interplay between cultural and linguistic factors on the one hand and conversational dynamics on the other.

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“…It has been shown that, during conversational interaction, speakers become more similar to their interlocutor along various acoustic-phonetic dimensions, such as consonants, vowel formants, vowel duration, and speech rate (see Wynn & Borrie, 2022 for a review). The same is true of sociolinguistic variables at other levels of the grammar as well: speakers tend to shift from their typical rate of variant use toward their interlocutors’ use of variants, as has been seen in English zero copula, invariant be , plural -s , third singular present -s , and possessive -s (Rickford & McNair-Knox, 1994); English ellipsis alternation (Nykiel, 2015); Swedish alveolar r (Nilsson, 2015); Scottish r (Llamas, Watt, & Johnson, 2009); and others.…”

Section: Introductionmentioning

confidence: 99%

“…One obstacle to comparing them is differences in the way that persistence and convergence have been operationalized: corpus persistence analyses have typically focused on a token-by-token analysis like the one we undertake here, whereas convergence is often measured by averaging over larger time windows. Recent work from Wynn and Borrie synthesizing the literature on conversational entrainment (i.e., convergence) in phonetics provided a helpful framework for understanding these differences as involving the level of entrainment, which they defined as “the temporal interval at which entrainment is measured” (2022:4). Although they distinguished between local (turn-level) and global (above the turn level), we interpret these levels as existing on a continuum, which the variationist and corpus linguistic repetitiveness literatures span.…”

Section: Introductionmentioning

confidence: 99%

Intra- and interspeaker repetitiveness in Chengdu Mandarin locative variation

Tamminga

2023

Lang Var Change

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In producing linguistic variation, language users display a tendency to reuse the same variant. This paper compares the empirical properties of different types of repetitiveness in a single case study: locative variation in Chengdu Mandarin. Using conversational data from sociolinguistic interviews, we ask whether within-speaker repetitiveness (persistence) and cross-speaker repetitiveness (convergence) behave similarly with respect to (1) their sensitivity to the linguistic similarity of the prime and target, and (2) their tendency to decline with greater temporal distance between the prime and target. Our results suggest that intraspeaker persistence and interspeaker convergence behave similarly in both respects. We therefore propose that repetitiveness has a common underlying mechanism within and across speakers and encourage future work aimed at testing this hypothesis across other variables and varieties.

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Classifying conversational entrainment of speech behavior: An expanded framework and review

Cited by 15 publications

References 73 publications

Does a Robot’s Gaze Behavior Affect Entrainment in HRI?

Does a Robot’s Gaze Behavior Affect Entrainment in HRI?

Language‐Specific Constraints on Conversation: Evidence from Danish and Norwegian

Intra- and interspeaker repetitiveness in Chengdu Mandarin locative variation

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