ArticlePDF Available

Resonance in dialogue: The interplay between intersubjective motivations and cognitive facilitation

August 2021
Language and Cognition 13(4):643–669

August 2021
13(4):643–669

DOI:10.1017/langcog.2021.16

License
CC BY 4.0

Authors:

Nele Põldvere

University of Oslo

Victoria Johansson

Kristianstad University

Carita Paradis

Lund University

Dialogic resonance, when speakers reproduce constructions from prior turns, is a compelling type of coordination in everyday conversation. This study takes its starting point in resonance in stance-taking sequences with the aim to account for the interplay between intersubjective motivations and cognitive facilitation in resonance production. It analyzes stance-taking sequences in the London–Lund Corpus 2, determining (i) the type of stance alignment (agreement or disagreement), and (ii) the time lapse between the stance-taking turns. The main findings are, firstly, that resonance is more likely than non-resonance to be used by speakers who express disagreement than agreement, which we interpret as a mitigating function of resonance, and, secondly, that the turn transitions are faster in resonating sequences due to cognitive activation in the prior turn. We propose that the face-saving intersubjective motivation of resonance combines with its facilitating cognitive effect to promote appeasing communication.

Content uploaded by Nele Põldvere

Content may be subject to copyright.

Available via license: CC BY 4.0

Content may be subject to copyright.

Language and Cognition 13 (2021), 643–669. doi:10.1017/langcog.2021.16

article, distributed under the terms of the Creative Commons Attribution licence (http://

creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and

reproduction in any medium, provided the original work is properly cited.

Resonance in dialogue: the interplay between

intersubjective motivations and cognitive facilitation*

NELE PÕLDVERE

Lund University and University of Oslo

VICTORIA JOHANSSON

and

CARITA PARADIS

Lund University

(Received 14 October 2020 –Revised 14 June 2021 –Accepted 21 July 2021 –

First published online 31 August 2021)

abstract

Dialogic resonance, when speakers reproduce constructions from prior

turns, is a compelling type of coordination in everyday conversation. This

study takes its starting point in resonance in stance-taking sequences with

the aim to account for the interplay between intersubjective motivations

and cognitive facilitation in resonance production. It analyzes stance-tak-

ing sequences in the London–Lund Corpus 2, determining (i) the type of

stance alignment (agreement or disagreement), and (ii) the time lapse

between the stance-taking turns. The main ﬁndings are, ﬁrstly, that reso-

nance is more likely than non-resonance to be used by speakers who express

disagreement than agreement, which we interpret as a mitigating function

of resonance, and, secondly, that the turn transitions are fasterin resonating

sequences due to cognitive activation in the prior turn. Wepropose that the

[*] We would like to thank John Du Bois, Mattias Heldner, and Kobin Kendrick for valuable

feedback during the preparation of this study, and the editor and two anonymous reviewers

for helpful comments on earlier versions of the manuscript. Many thanks also to Simone

Löhndorf for serving as the reliability coder, Maria Graziano for assistance with ELAN,

and Joost van de Weijer and Sara Farshchi for their support with statistics. The compi-

lation of LLC–2 has largely been made possible by generous grants from the Linnaeus

Centre for Thinking in Time: Cognition, Communication, and Learning, ﬁnanced by the

Swedish Research Council (grant no. 349-2007-8695), and the Erik Philip-Sörensen

Foundation. Address for correspondence: email: nele.poldvere@englund.lu.se

643

Cambridge Core terms of use, available at https://www.cambridge.org/core/terms. https://doi.org/10.1017/langcog.2021.16

Downloaded from https://www.cambridge.org/core. IP address: 193.157.111.124, on 06 Nov 2021 at 10:15:16, subject to the

face-saving intersubjective motivation of resonance combines with its

facilitating cognitive eﬀect to promote appeasing communication.

keywords: stance-taking, disagreement, intersubjective alignment,

cognitive activation, turn transitions, London–Lund Corpus 2

1. Introduction

When speakers are engaged in everyday conversation, they constantly negoti-

ate and coordinate their stances to establish mutual understanding of what the

conversation is about, and they do so in a turn-taking fashion (Brennan &

Clark, 1996; Clark, 1996; Du Bois & Giora, 2014; Fusaroli & Tylén, 2012;

Linell, 2009; Põldvere & Paradis, 2019,2020). Based on conversational data

from the London–Lund Corpus 2 (LLC–2) of spoken British English

(Põldvere et al., 2021, in press), this study focuses on a compelling type of

coordination, namely dialogic resonance in stance alignment in

speaker turns. Following Du Bois (2007,2014), we deﬁne dialogic resonance

as the reproduction of constructions across speaker turns. Stance alignment in

this study ranges from agreement to disagreement. For instance, consider the

utterances in bold in (1), where speaker A resonates with B’s prior contribution

at the level of both forms and meanings (e.g., the stance adverb particularly, the

negated constructions, the metonymical reformulation of interested in religious

things into up at seven AM). In contrast, if A’s response had been a simple no,

the utterances would not have included any resonating items.

(1) A: I’m surprised that she’s unaware of the programme at seven AM on Sunday which

is called uh it’s called Sunday

B: well why should she be she hasn’t hitherto been particularly interested in

religious things [has she]

A: [you mean] she hasn’t particularly been up at seven AM

B: no that too

The stance alignment between the turns taken by A and B in (1) is one of

disagreement in that there is a certain clash between the stances that the two

speakers take vis-à-vis the person talked about. Also, A’s response is given very

quickly after B’s prior turn (the square brackets indicate an overlap), which is

intriguing because such a turn-taking pattern has previously been considered

to be more common in agreement than disagreement (Pomerantz, 1984).

Resonance in dialogue has been dealt with in both linguistics and psychology,

with slightly diﬀerent yet overlapping foci and terminologies. For instance, Du

Bois (2014) argues that resonance is an intersubjectively motivated phenomenon

that occurs because speakers want to engage with the words of their interlocutors

for various communicative reasons (see Clark, 1996, for similar views). Garrod

and Pickering (2004), on the other hand, regard the phenomenon as an automatic

cognitive process whereby the preceding expression primesthe reuse of the same

644

˜ldvere et al.

Downloaded from https://www.cambridge.org/core. IP address: 193.157.111.124, on 06 Nov 2021 at 10:15:16, subject to the Cambridge Core

linguistic representations by the next speaker. Both lines of research, however,

argue that resonance hasa facilitating eﬀect due tothe cognitive activation in the

mind of the second speaker by the prior speaker’s turn, a phenomenon that may

also have the eﬀect of speeding up turn transitions. It is precisely at this juncture

that our study contributes new knowledge with an approach that straddles the

gap between communicative and cognitive aspects of resonance production.

Using data consisting of stance-taking sequences in everyday face-to-face

conversation in LLC–2, we examine why and when speakers resonate with

each other’s contributions. The aim is to further our understanding of the

intersubjective motivations and cognitive facilitation of dialogic resonance in

stance-taking turns, where cognitive facilitation is operationalized as the time it

takes for speakers to respond to the interlocutor’s prior stance. Two questions

are at the core of this study.

1. Is resonance more likely than non-resonance to appear in disagreement

than in agreement? If so, why may this be the case?

2. Does resonance lead to faster turn transitions than non-resonance and, if

so, why may this be the case? Are there diﬀerences in this respect between

agreement and disagreement?

The background sections provide more information about dialogic resonance

(Section 2) and the timing of turns in conversation (Section 3).

2. Dialogic resonance

Dialogic resonance emerges “when speakers selectively reproduce aspects of

prior utterances, and when recipients recognize the resulting parallelisms and

draw inferences from them”(Du Bois, 2014, p. 359), thus using it as a way of

establishing common ground and interpersonal engagement between interlocu-

tors (seealso, e.g., Brône & Zima, 2014; Dori-Hacohen, 2017;DuBois,2007;Du

Bois et al., 2014;Maschler&Nir,2014;Nir,2017; Nir et al., 2014;Nir&Zima,

2017; Zima et al., 2009). A particularly compelling environment for resonance is

stance-taking. In the present study, stance is understood as an umbrella term for

a range of linguistic expressions that convey (i) speakers’opinions, viewpoints,

and attitudes towards objects, states, and events (e.g., happy,unsafe,eﬀective),

(ii) assessments of certainty, reliability, and limitations of what is conveyed (e.g.,

Ithink,obviously,must), and (iii) comments on the discourse itself (e.g., honestly,

with all due respect,ﬁnally; Chafe & Nichols, 1986;Fuoli,2017;Hunston&

Thompson, 2000; Marín-Arrese, 2015;Martin&White,2005;Palmer,2001;

Põldvere et al., 2016;Simakietal.,2017). While there is great variability in our

data regarding the functions that these expressions perform, they all contribute to

the three key components of stance-taking as proposed by Du Bois (2007):

evaluation, positioning, and alignment. These three components have three

645

resonance in dialogue

Downloaded from https://www.cambridge.org/core. IP address: 193.157.111.124, on 06 Nov 2021 at 10:15:16, subject to the Cambridge Core

diﬀerent consequences for the stance-taking act. Figure 1 visualizes a stance-

taking act between two subjects, where the subjects (i) evaluate an object,

(ii) position themselves, and (iii) align with each other. Du Bois deﬁnes

alignment as “the act of calibrating the relationship between two stances,

and by implication between two stancetakers”(2007, p. 144). The intersub-

jective alignment between the stances may range from agreement to disagree-

ment, and it may be made more noticeable by formal and semantic mappings

from one speaker to the next through dialogic resonance.

Consider (2) as a concrete example of the stance triangle and resonance.

involves two speakers, Alice and Mary, who evaluate the same stance object

(a third person and her intentions to carry out an action). Alice produces a so-

called stance lead in which she expresses uncertainty about the stance object

(I don’t know if she’ddoit). The stance lead is followed by a stance follow in

which Mary expresses agreement with Alice, while at the same time formally

resonating with her (I don’t know if she would either). Formal resonance emerges

when elements from the prior turn are reused through repetition and minor

changes (see Dori-Hacohen, 2017; Du Bois, 2007,2010).

The resonance in

Fig. 1: The stance triangle represents the stance-taking act (Du Bois, 2007, p. 163).

[1] The following symbols and conventions are important for interpreting the examples in this

section (Du Bois et al., 1993). First, each line in the transcriptions corresponds to one

intonation unit. Second, pausedurations are measured in seconds. Third, overlapping speech

is represented by square brackets and prosodic prominence by the caret (^). Finally,full stops

correspond to ﬁnal intonation contours and commas to continuing intonation contours.

[2] Note, however, that what we call ‘formal resonance’is called ‘presupposing resonance’in

Du Bois (2010).

646

˜ldvere et al.

Downloaded from https://www.cambridge.org/core. IP address: 193.157.111.124, on 06 Nov 2021 at 10:15:16, subject to the Cambridge Core

(2) is further highlighted through either, which is tagged on to mark agreement.

In cases of disagreement expressed through formal resonance, markers of

opposition such as negation (e.g., not,never,hardly) or conventionalized

antonyms (e.g., good–bad,hot–cold,slow–fast) may be used by speakers.

(2) Extracted from Du Bois (2007, p. 160)

ALICE: I don’t know if she’d do it.

(0.6)

MARY: I don’t know if she would either.

Within resonance research, much of the work so far has focused on dialogic

exchanges where the speakers express some kind of stance diﬀerential (e.g.,

Brône & Zima, 2014; Dori-Hacohen, 2017; Zima et al., 2009), thus suggesting

that resonance is a fruitful way to express disagreement in dialogue. Consider

(3), where two speakers, Joanne and Lenore, are talking about a mutual

acquaintance who is a recovering alcoholic. The parallelism in this example

is between the utterances yet he’s still healthy and he’s still walking around.

(3) Extracted from Du Bois (2014, p. 368)

JOANNE: yet he’s still ^healthy.

He reminds me [of my ^brother].

LENORE: [He’s still walking] ^around,

I don’t know how ^healthy he is.

On the one hand, the utterances in (3) are framed by the phrase he’s still (formal

resonance), which identiﬁes the stance object to be evaluated. On the other

hand, the prosodically focal element, the adjective healthy, in Joanne’s utter-

ance resonates with the verb phrase walking around in Lenore’s utterance. Out

of context, these expressions have very little in common, but the dialogic

juxtaposition of healthy and walking around invites the inference that, in this

particular context, the phrases are understood as related to each other through

opposition. They are meanings at opposite poles of health (healthy 6¼

walking around), but since they are not conventionalized antonyms, they

require contextual boosting to be understood as opposites of the same meaning

dimension (Paradis & Willners, 2011; van de Weijer et al., 2014). We refer to

this type of resonance as semantic resonance in that it involves resonating

semantic structures, i.e., opposites or near-synonyms depending on whether

the speakers express disagreement or agreement, respectively.

In the case of

agreement, it is again the focal elements that are near-synonyms (e.g., confusing

and wobbly in it’s a little bit confusing!t is all a bit wobbly; see Section 5).

Resonance, and particularly semantic resonance, is an eﬀective way to

express disagreement in a range of discourse contexts. Brône and Zima

(2014) and Zima et al. (2009), for instance, show that semantic resonance is

[3] Note that this type of resonance is called ‘creative resonance’in Du Bois (2010).

647

resonance in dialogue

Downloaded from https://www.cambridge.org/core. IP address: 193.157.111.124, on 06 Nov 2021 at 10:15:16, subject to the Cambridge Core

commonly used in parliamentary debates to strike one’s political opponents

with a skillful play on the meaning potential of constructions. As for everyday

conversation, which typically is much less adversarial, a diﬀerent pattern seems

to emerge. Based on a comprehensive analysis of a conversation in Hebrew

carried out during a car ride, Dori-Hacohen (2017) shows that semantic

resonance is an eﬀective way to reject requests for driving directions and to

enhance distance between the interlocutors. However, the focus of the study is

on a very speciﬁc type of action (i.e., requests for driving directions) and a

single conversation, which makes us hesitant to interpret the results as trans-

ferrable to everyday conversation in general.

The view of resonance adopted by Du Bois is in line with the general view of

language by Clark (1996), namely as intentional joint action undertaken by

speakers with speciﬁc goals in mind. According to Clark, speakers are oriented

towards a common goal, and they actively monitor and infer each other’s

intentions and assumptions to achieve this goal. However, Du Bois (2014)

also acknowledges the facilitating role of the cognitive process of priming in

resonance. According to Du Bois, lexical and structural priming, in particular,

create cognitive conditions that trigger the reuse of linguistic forms and

structures, but the nature of the role of cognitive facilitation in resonance

production has not been backed up by empirical evidence. In contrast, priming

is central in interactive alignment theory in cognitive psychology (e.g., Garrod

& Pickering, 2004; Pickering & Garrod, 2004), but note that, in their theory,

the term ‘alignment’refers to the reuse of prior linguistic material (i.e., what we

refer to as resonance), not to an intersubjective relation between two stances as

understood in this study (see also Rasenberg et al., 2020, for a review of other

related theories). According to Garrod and Pickering (2004), interlocutors

come to understand a conversation in the same way due to an automatic process

whereby the reuse of prior material at lower levels of linguistic representation,

ranging from words and syntax to semantic and pragmatic relations, leads to

mutual understanding at the critical level of the situation model. Moreover, the

primed linguistic representations become available to interlocutors with

reduced cognitive eﬀort. While Pickering and Garrod (2005) contend that

“the pressures of actual conversation …mean that in practice interlocutors

perform very little ‘other modelling’” (2005, p. 87), they do not deny the role of

intentional processes. Since Garrod and Pickering’s seminal publication from

2004, interactive alignment has come to be used in many disciplines as a cover

term for repetition, and this more recent literature has not necessarily been

committed to the original automatic view or it has not taken a clear stand in the

intentional vs. automatic debate (e.g., Allen et al., 2011; Dideriksen et al.,

2019; Fusaroli et al., 2012). In this study, we have decided to adhere to the

original version of interactive alignment as proposed by Garrod and Pickering

in our theoretical discussion.

648

˜ldvere et al.

Downloaded from https://www.cambridge.org/core. IP address: 193.157.111.124, on 06 Nov 2021 at 10:15:16, subject to the Cambridge Core

3. Timing of turns

Spoken interaction is characterized by rapid transitions of speaker turns that,

according to the inﬂuential model by Sacks et al. (1974), overwhelmingly occur

with no gaps and no overlaps. This means that speakers avoid starting their

turns too early (perceived overlaps) or too late (perceived gaps). While the

study by Sacks et al. was largely based on qualitative observations of spoken

interaction, more recent corpus studies on a range of the world’s languages

have conﬁrmed that the majority of turn transitions in conversation take place

within the time course of around 200 to 300 ms (e.g., Heldner & Edlund, 2010;

Levinson & Torreira, 2015; Roberts et al., 2015; Stivers et al., 2009). This is

interesting in the light of the fact that psycholinguistic research has shown that

it takes around 600 ms to produce a single word (e.g., Levelt et al., 1999), which

is an indication that speakers project the end of the incoming turn to then

launch their own turn immediately (Sacks et al., 1974). Experimental studies

have shown that speakers start planning their turns as soon as they have

gathered enough information about the incoming turn; the earlier this is made

possible, the faster the upcoming turn (e.g., Barthel et al., 2016).

The timing of turns in conversation depends on many diﬀerent communi-

cative and cognitive factors. Much of the work on this topic so far has focused

on question–response sequences. For example, Meyer et al. (2018) found

strong eﬀects of response length and response polarity on the timing of

responses to polar questions. They found that the response latencies were

shorter for one-word responses (yes and no) and longer in responses where

yes and no were further qualiﬁed in the second part of the utterance. This

indicates that the participants did not plan the long responses in a truly

incremental fashion but instead “carried out at least some of the planning for

the second part of the utterance before responding”(2018, p. 9), especially

since they rarely paused between the ﬁrst and the second part of the response.

Furthermore, regardless of length, negative responses to polar questions were

given more slowly than positive responses, a result that suggests some reluc-

tance on the part of the participants to provide a negative response (see also

Stivers et al., 2009).

This result is in line with the notion of preference organization in conver-

sation analytic and interactional linguistic research (e.g., Atkinson & Heritage,

1984; Pomerantz, 1984; Schegloﬀ,1988), which reports that there is a tendency

for preferred responses (e.g., agreement) to occur relatively early and often in

overlap with the prior turn, and for dispreferred responses (e.g., disagreement)

to occur after a delay. However, when Kendrick and Torreira (2015) set out to

quantitatively verify these claims based on a sample of acceptances and rejec-

tions in corpora of telephone calls, they instead found that the timing of turns

was not so much a function of the action performed in the turn (acceptance or

649

resonance in dialogue

Downloaded from https://www.cambridge.org/core. IP address: 193.157.111.124, on 06 Nov 2021 at 10:15:16, subject to the Cambridge Core

rejection) as it was of the way the turn had been designed. With the exception of

long gaps of 700 to 800 ms after which the responses were almost exclusively

rejections, both positive and negative response tokens (yes and no) occurred

signiﬁcantly earlier than qualiﬁed acceptances (e.g., yes, but …) and rejections

(e.g., no, I don’t think so). Roberts et al. (2015) found a similarly weak eﬀect of

preference organization in their analysis of a range of utterance types in

telephone calls from the Switchboard corpus (see also Robinson, 2020, for

issues with the two-way distinction between preferred and dispreferred

responses).

To the best of our knowledge, no corpus or experimental studies have

investigated the eﬀect of dialogic resonance on the timing of turns in conver-

sation. A mention in passing is made in Meyer et al. (2018), who acknowledge

that long utterances may be initiated faster if they are activated in the preceding

context (see also Garrod & Pickering, 2015, for similar observations), but no

empirical evidence is provided to support this claim. This is in spite of the fact

that resonance seems essential in conversational turn-taking due to the very

tight time constraints under which conversation operates, and the facilitating

eﬀect that resonance may have on turn uptake (cf. Du Bois et al., 2014; Garrod

& Pickering, 2004). Concepts that have already been mentioned in the prior

discourse are more accessible and therefore produced earlier in order to

minimize cognitive demands on the next speaker (Ariel, 1988; Tachihara &

Goldberg, 2020). The shorter time it takes for speakers to resonate with each

other may also shed light on the role of cognitive facilitation in resonance

production. However, as Nir and Zima (2017) put it, this does not mean that

resonance should be reduced to lower cognitive eﬀort but that intentional

processes are also at play: “when resonance is created between utterances,

speakers (or writers) not only make use of the linguistic resources that are

already available but they create new meaning by re-contextualizing these

resources”(2017, p. 7). This is particularly true of semantic resonance, which

can be expected to be more cognitively demanding for the next speaker than

formal resonance due to diﬀerences in mapping relations.

4. The present study

While previous research has acknowledged a reciprocal relationship between

intersubjective motivations and cognitive facilitation in dialogic resonance,

they have not expanded on, or empirically tested, how communicative and

cognitive aspects relate to each other in resonance production. Based on data of

stance-taking sequences in everyday face-to-face conversation, this corpus-

based study takes an interest in both aspects in order to bridge the gap between

interactional linguistic and cognitive approaches to resonance.

650

˜ldvere et al.

Downloaded from https://www.cambridge.org/core. IP address: 193.157.111.124, on 06 Nov 2021 at 10:15:16, subject to the Cambridge Core

Based on the literature, we make two predictions. Prediction 1 relates to the

intersubjective motivations of resonance, explored through the type of alignment

in the stance-taking sequence. The prediction is that resonance is more likely to

be used by speakers in disagreement, while non-resonance is the preferred option

in agreement. Support for Prediction 1 comes from previous work on resonance

in contesting situations (Brône & Zima, 2014; Dori-Hacohen, 2017; Zima et al.,

2009).

Prediction 2 relates to the role of cognitive facilitation in resonance, which

we operationalize by measuring the time it takes for speakers to respond to the

interlocutor’s prior stance. The prediction is that, due to the facilitating eﬀect

of reusing prior linguistic material, transitions between speaker turns are faster

in resonating sequences than when the turns are constructed from scratch. We

expect the eﬀect to be observable both for formal and semantic resonance, but

to a lesser extent for semantic resonance, which relies on meaning mappings

only. This said, the short latencies observed for response tokens such as yes and

no (Kendrick & Torreira, 2015; Meyer et al., 2018) suggest that formal

resonance does not trump the ease of production of these short and highly

frequent linguistic expressions. Therefore, response tokens are set in contrast

to another type of non-resonating sequences, namely elaborated responses,

which are longer and may or may not contain a response token (e.g., you need to

moderate the length !yeah that was a long essay; see Section 5). They corre-

spond roughly to long responses in Meyer et al. (2018) and qualiﬁed accep-

tances and rejections in Kendrick and Torreira (2015). The speciﬁc prediction

we make is that response tokens are produced the fastest, followed by formal

and semantic resonance, and, ﬁnally, by elaborated responses of non-reso-

nance. Due to conﬂicting evidence in the literature regarding preference

organization and the timing of turns in conversation, the eﬀect of intersubjec-

tive alignment on the duration of turn transitions in this study is presented as

an exploratory question rather than a prediction.

5. Methods

5.1. the sample

The data are from a new corpus of spoken British English, the London–Lund

Corpus 2 (LLC–2), recorded between 2014 and 2019. LLC–2contains

approximately 500,000 words stored in 100 texts of 5,000 words each, and

corresponding audio ﬁles.Thesampledrawnforthisstudycomesfromface-

to-face conversation, the most important conversational setting in LLC–2.

In order to control for the number of speakers, only dyadic conversations

were included. The sample contains 20 texts of 5,000 words each, totaling

some 100,000 words. While 12 of the texts correspond to one single

651

resonance in dialogue

Downloaded from https://www.cambridge.org/core. IP address: 193.157.111.124, on 06 Nov 2021 at 10:15:16, subject to the Cambridge Core

conversation, eight texts contain two diﬀerent conversations of 2,500 words

each. This means that the ﬁnal sample contains 28 diﬀerent conversations

among 48 unique speakers (age range 18–71; M=36). Among the 28 conver-

sations, 11 are mixed between male and female, 14 are all female and three are

all male.

5.2. extracting the stance-taking sequences

The basic unit of analysis in this study is the stance-taking sequence, which

comprises two utterances: the stance lead (the ﬁrst utterance produced by the

ﬁrst speaker) and the stance follow (the second utterance produced by the

second speaker; Du Bois, 2007). A stance-taking sequence may perform a

range of functions in discourse (e.g., aﬀect, epistemic modality, evidential-

ity), but it must make reference to the evaluation, positioning, and alignment

of the stance-taking act (see Section 2 above). Example (4) illustrates a stance-

taking sequence consisting of the stance lead thatwasabitoddand the stance

follow yeah I found it quite strange, in which speaker B expresses agreement

with the evaluation of A, and where both speakers simultaneously position

themselves as the stance-takers. Note that all examples in this section are

from LLC–2.

(4) A: that was a bit odd

B: yeah I found it quite strange

Intersubjective alignment may also be expressed by response tokens only, in

particular response tokens that signal (dis)agreement and engagement with the

stance lead (e.g., yeah,no,brilliant; see O’Keeﬀe & Adolphs, 2008). We

excluded response tokens that are primarily used for discourse organizational

purposes (e.g., mhm,uh huh,right) because they do not express (dis)agreement.

Since some response tokens such as yeah are ambiguous between the two

readings, prosodic prominence was considered a criterion of agreement

(cf. Müller, 1996). This was determined auditorily or, if necessary, instru-

mentally in Praat (Boersma, 2001). We also excluded response tokens that

position the stance-taker as not knowing (I don’t know).

In order to obtain accurate measurements of the durations of turn transi-

tions, we decided to limit the analysis to certain contexts only. It was important

to make sure that any diﬀerence in the timing of the stance-taking sequences

was due to the factors tested in this study (resonance and alignment) and not to

some confounding factors. Thus, the stance-taking sequences included in the

study had to meet a number of criteria that, in previous research, have been

found to either speed up or slow down turn transitions. Table 1 lists all the

criteria (column 1). Columns 2 and 3 provide examples of the diﬀerent kinds of

stance-taking sequences (in italics) that were included and excluded,

652

˜ldvere et al.

Downloaded from https://www.cambridge.org/core. IP address: 193.157.111.124, on 06 Nov 2021 at 10:15:16, subject to the Cambridge Core

table 1. Criteria for the inclusion of stance-taking sequences in the analysis based on previous research on factors that are

expected to either speed up or slow down turn transitions (the first and the second part of the table, respectively). The criteria

are accompanied by examples from LLC–2 where the stance-taking sequences are given in italics and the square brackets

indicate overlaps.

Expected to speed up turn transitions

Criteria for inclusion Examples included Examples excluded

–Stance lead is a statement or exclamation

Questions anticipate a response and may elicit

early responses, except for overlapping tag

questions (see Stivers & Enﬁeld, 2010, for

question types and Holler & Kendrick, 2015,

on early gaze shifts)

A: she hasn’t hitherto been particularly

interested in religious things [has she]

B: [you mean]she hasn’t particularly been

up at seven AM

A: but did they have to kind of knock them

[out as well or]

B: [no no uhm]

–Stance follow is not chorally co-produced with

the stance lead

Choral co-production is strongly correlated with

overlap (Lerner, 2002)

A: I suppose because they look reptilian

B: I guess that hippos don’t look obviously

dangerous

A: the other thing to do obviously would be to

do an [acoustic analysis]

B: [acoustic]

Expected to slow down turn transitions

Criteria for inclusion Examples included Examples excluded

–Stance lead is longer than one word

Turns shorter than 700 ms lead to slower turn

transitions (Roberts et al., 2015); observation of

the data revealed that <700 ms turns tend to

contain only one word

A: not bitchy

B: so nice

A: healthy <pause/>

B: healthy

653

resonance in dialogue

Downloaded from https://www.cambridge.org/core. IP address: 193.157.111.124, on 06 Nov 2021 at 10:15:16, subject to the Cambridge Core

table 1. Continued

Expected to slow down turn transitions

Criteria for inclusion Examples included Examples excluded

–Stance lead is a complete utterance, including turn-

ﬁnal particles

Speakers orient to prosodic, syntactic and semantic

cues to predict turn endings (Sacks et al., 1974);

incomplete utterances may lead speakers to react to

silence instead (Heldner & Edlund, 2010)

A: otherwise I assume they would’ve knocked

them down so

B: yeah

A: but they never <pause/>

B: yeah

–Stance lead does not overlap with the prior turn

Prior overlap creates delays in responding

A: I’m not sure why I was wearing it

B: well we just need to wear some brown things

and uh like a bear mask

A: mm I don’t really want to wear a mask

A: I wouldn’t say he like knows me in the

way that Thomas knows [me like he

doesn’t get who I am]

B: [of course not because he’s too self-

centred]

A: yeah he doesn’t care

–Stance lead and stance follow are adjacent

utterances

An intervening utterance may inhibit the second

speaker from launching his/her turn until the

intervening utterance has come to an end, unless

the stance follow is produced shortly after the

stance lead (even if in overlap with the longer turn)

A: I mean it’s a huge thing and [I think it’d

be] really exciting to go

B: [yeah]

A: yeah that’s The New Yorker whereas

The New York Times is a newspaper

B: I’m not sure that it was The New Yorker

654

˜ldvere et al.

Downloaded from https://www.cambridge.org/core. IP address: 193.157.111.124, on 06 Nov 2021 at 10:15:16, subject to the Cambridge Core

respectively. Horizontally, the table is divided into two parts. The ﬁrst part

lists the criteria that were expected to speed up turn transitions, and the second

part lists the criteria that were expected to slow down the turn transitions. For

example, the ﬁrst criterion in Table 1 states that the stance lead had to be a

statement or an exclamation, which means that it could not fall under any of the

question types identiﬁed in Stivers and Enﬁeld (2010). The reason for this is

that questions anticipate a response and may elicit earlier responses from the

interlocutor than utterance types where the interlocutor’s response is often not

necessary, such as stance-taking sequences (see Holler & Kendrick, 2015,on

early gaze shifts in questions). An exception was made for tag questions that

were uttered in overlap with the stance follow, because in those cases the

second speaker did not react to the tag question but to what came before.

The example in the second column meets this criterion and was included in the

analysis, while the yes–no question in the third column was excluded.

AscanbeseeninTable 1, none of the criteria make reference to non-verbal

turn-yielding cues such as gaze, hand gestures, and facial expressions (e.g.,

Holler et al., 2017; Stivers et al., 2009). This is because there is no video-

recording in LLC–2. However, the focus of this study on verbal communi-

cation, and the rigorous manual treatment of a large number of verbal cues as

demonstrated in Table 1, to some extent compensates for the lack of video

material. Also, we acknowledge the possible inﬂuence of other communica-

tive and cognitive factors on the timing of turns in conversation (see, e.g.,

Roberts et al., 2015), but the use of corpus methods in this study limited the

number of confounding factors for which we could control. Thus, the criteria

in Table 1 provide the constraints for what kinds of sequences to include in

this study.

The stance-taking sequences were extracted from the sample in the follow-

ing way. First, the 28 conversations were read in full in order to identify stance-

taking sequences that also included resonance (see below). We found 263 such

sequences. We then extracted ﬁve-minute excerpts from the 28 conversations,

and from those excerpts non-resonating stance-taking sequences were

retrieved; all in all, we found 319 non-resonating sequences. Non-resonance

is much more common and therefore there was no need to scrutinize whole

texts to obtain such sequences. Section 5.3 describes how the sequences were

classiﬁed.

5.3. the classification of dialogic resonance and

intersubjective alignment

The classiﬁcation of the stance-taking sequences was carried out in ELAN 5.4,

which is a multimodal annotation tool that allows for a multi-layered descrip-

tion of digital research data (Wittenburg et al., 2006). ELAN was chosen

655

resonance in dialogue

Downloaded from https://www.cambridge.org/core. IP address: 193.157.111.124, on 06 Nov 2021 at 10:15:16, subject to the Cambridge Core

because of the multimodal nature of the study, involving both the classiﬁcation

of the stance-taking sequences and measurements of the turn transitions.

A detailed and context-speciﬁc annotation manual was devised for this pur-

pose.

This sub-section provides a brief overview of the ﬁrst part of the analysis

and how the stance-taking sequences were classiﬁed in terms of (i) dialogic

resonance and (ii) intersubjective alignment.

5.3.1. The classiﬁcation of dialogic resonance

Two diﬀerent schemes were devised for classifying the stance-taking

sequences: a broad classiﬁcation and a ﬁne-grained classiﬁcation. The broad

classiﬁcation corresponds to Prediction 1 about the intersubjective motiva-

tions of dialogic resonance, where a distinction was made between resonance

and non-resonance (see Section 4 above). The key method for distinguishing

between resonating and non-resonating stance-taking sequences was to try

to place them in a diagraph, deﬁned as “a higher-order, supra-sentential

syntactic structure that emerges from the structural coupling of two or more

utterances (or utterance portions), through the mapping of a structured

array of resonance relations between them”(Du Bois, 2014,p.376).The

diagraph helped us visualize and detect mappings across the utterances that

would otherwise go unnoticed. In order to qualify as an instance of reso-

nance, the utterances in the stance-taking sequence had to map onto each

other in the diagraph. In case the utterances resisted being placed in a

diagraph, the sequence was considered non-resonating instead. For exam-

ple, the stance-taking sequence in (5) meets this criterion, while the sequence

in (6) does not.

(5) A: it ’s a little bit confusing

B: it is all a bit wobbly

(6) A: you need to moderate the length

B: yeah that was a long essay

Next, the ﬁne-grained classiﬁcation corresponds to Prediction 2 about the

cognitive facilitation of dialogic resonance, where further distinctions of (non)-

resonance were made. As for resonance, we made a distinction between formal

and semantic resonance (see Section 2 above and the annotation manual for

details). Example (5), for instance, is a case of semantic resonance, because

confusing and wobbly may not be immediately obvious candidates for near-

synonymy out of context. They require contextual boosting to be understood

[4] The annotation manual is available online at <https://snd.gu.se/en>.

656

˜ldvere et al.

Downloaded from https://www.cambridge.org/core. IP address: 193.157.111.124, on 06 Nov 2021 at 10:15:16, subject to the Cambridge Core

as such. We also made a distinction between two types of non-resonance:

elaborated responses and response tokens. Stance-taking sequences of the

former kind cannot be placed in a diagraph because of major structural

diﬀerences between the utterances, as shown in (6), while in the case of

response tokens (e.g., if B’s response had been a simple yeah), resonance is

by deﬁnition impossible.

5.3.2. The classiﬁcation of intersubjective alignment

The stance-taking sequences were then classiﬁed in terms of the type of

intersubjective alignment. For this, a distinction was made between agreement

and disagreement (see the annotation manual). Although we agree with Du

Bois (2007) that intersubjective alignment is not a strict binary choice between

the two types of alignment, the distinction was necessary in order to obtain

better control over the data.

To assess the reliability of the analysis above, a series of inter-rater reliability

tests were carried out based on our annotation and the annotation of ~10% of

the stance-taking sequences by a research assistant with no prior experience in

dialogic resonance. Comparisons of the annotation of resonance revealed

94.83% agreement for the broad classiﬁcation, yielding a Cohen’s chance-

corrected kappa coeﬃcient of .891 (‘almost perfect agreement’according to

the scale of Landis & Koch, 1977), and 89.66% agreement for the ﬁne-grained

classiﬁcation (k=.824; ‘almost perfect agreement’). Disagreements between

the annotators were discussed and resolved together. Intersubjective align-

ment yielded 100% agreement.

5.4. measuring the turn transitions

This sub-section concerns the second part of the analysis in which durations of

transitions from the stance lead to the stance follow were measured in ELAN.

The measurements were made from the last acoustic signal of the stance lead to

the ﬁrst acoustic signal of the stance follow, excluding vocal noises such as out-

breaths, in-breaths, and clicks (see Kendrick & Torreira, 2015). The transition

was either a gap or an overlap and was given either a positive or a negative value,

respectively. Very long gaps (longer than 2800 ms) and very long overlaps

(longer than –2800 ms; e.g., –3000 ms) were discarded from the analysis (~1%

of the data; cf. Roberts et al., 2015), leaving us with 260 resonating stance-

taking sequences and 316 non-resonating sequences.

To assess the reliability of our measurements, a research assistant mea-

sured the turn transitions of ~10% of the stance-taking sequences in ELAN

following the annotation manual. A comparison between the research

657

resonance in dialogue

Downloaded from https://www.cambridge.org/core. IP address: 193.157.111.124, on 06 Nov 2021 at 10:15:16, subject to the Cambridge Core

assistant’s and our measurements yielded a high degree of intraclass corre-

lation (ICC(1) =.96).

5.5. statistical analysis

The statistical analysis of the data was conducted in RStudio (version 1.0.136;

R Core Team, 2014). The plots were generated using the ggplot2 package, and

we ﬁtted the mixed-eﬀects regression models to our data using the glmer

(logistic) and lmer (linear) functions of the lme4 package (Bates et al., 2015).

Models of diﬀerent complexity were created and the model with the best

predictive accuracy, i.e., with the lowest AIC value, was chosen. The model

comparisons were made using the AICcmodavg package. The best model for

the logistic regression analysis had intersubjective alignment as the dependent

variable and dialogic resonance as the ﬁxed eﬀect, with by-speaker (the second

speaker) random slopes and by-conversation random intercepts. In the best

model for the linear regression analysis, duration was the dependent variable,

and resonance and alignment the ﬁxed eﬀects, with by-speaker (the second

speaker) and by-conversation random intercepts. Additionally, in the case of

the second model, we used the multcomp package (Hothorn et al., 2008) to carry

out six pairwise comparisons between levels of the ﬁxed eﬀects.

6. Results

This section reports the results of the descriptive and inferential statistical

analyses of the 260 resonating stance-taking sequences and 316 non-resonating

sequences.

6.1. the association between dialogic resonance and

intersubjective alignment

To test Prediction 1, we based the analysis on the broad classiﬁcation of

(non)-resonance as described in Section 5 above. Speciﬁcally, we studied the

distribution of the two types of intersubjective alignment –agreement and

disagreement –across the broad categories of resonance and non-resonance.

The results show that, while 35% (n=92) of the resonating stance-taking

sequences appear in disagreement, only 11% (n=35) of the non-resonating

sequences do. The mixed-eﬀects model conﬁrmed a signiﬁcant association

between resonance and disagreement (ß=1.8139, SE =0.5057, z=3.587,

p< .001), thus providing full support for the prediction that resonance is more

likely than non-resonance to appear in disagreement than agreement.

[5] The ﬁnal models for both analyses are available online at <https://osf.io/za7dk>.

658

˜ldvere et al.

Downloaded from https://www.cambridge.org/core. IP address: 193.157.111.124, on 06 Nov 2021 at 10:15:16, subject to the Cambridge Core

6.2. the effects of dialogic resonance and

intersubjective alignment on the duration of turn

transitions

Next, we tested Prediction 2 about the eﬀects of dialogic resonance and

intersubjective alignment on the duration of turn transitions. The analysis

was based on the ﬁne-grained classiﬁcation of (non)-resonance, which included

distinctions between the two types of resonance, formal and semantic, and

response tokens and elaborated responses of non-resonance. Intersubjective

alignment remained the same, i.e., agreement and disagreement. All combi-

nations of the ﬁxed eﬀects had an observed frequency of at least 10.

Figure 2 shows density plots of the durations of turn transitions for (non)-

resonance and intersubjective alignment. The top panels represent the distri-

butions (in ms) of formal and semantic resonance and the bottom panels the

distributions of response tokens and elaborated responses of non-resonance.

The vertical dotted lines are the mean durations. According to the observed

values of central tendency, the fastest turn transitions were attested for

response tokens (M=–56.71, Mdn =40.00, SD =638.33) and the slowest

for elaborated responses (M=605.21, Mdn =526.50, SD =554.39). Of the

two types of resonance, formal resonance was produced faster (M=114.13,

Fig. 2: The distribution of the durations of turn transitions (in ms) for formal and semantic

resonance (top panels), and response tokens and elaborated responses of non-resonance (bottom

panels). The vertical dotted lines represent the mean durations. The dark gray distributions in

each panel correspond to agreement and the light gray distributions to disagreement. The

jittered rugs below each panel display the individual data points.

659

resonance in dialogue

Downloaded from https://www.cambridge.org/core. IP address: 193.157.111.124, on 06 Nov 2021 at 10:15:16, subject to the Cambridge Core

Mdn =67.00, SD =605.25) than semantic resonance (M=253.75, Mdn =

211.00, SD =789.28). The jittered rugs below each panel demonstrate how the

density plots were created based on the individual data points. Each panel in

Figure 2 also shows a comparison of agreement (dark gray) and disagreement

(light gray). In all cases, there are noticeable diﬀerences in the distribution of

the two types of intersubjective alignment with a concentration of disagree-

ment to the right, thus suggesting slower turn transitions.

The results of the mixed-eﬀectsmodel provide partial support for Prediction

2. The prediction was that resonance, and particularly formal resonance, is

produced faster than elaborated responses of non-resonance but slower than

response tokens. The results also provide a positive answer to the open question

of whether or not there are diﬀerences in timing between agreement and

disagreement. Speciﬁcally, the model revealed a signiﬁcant main eﬀect of inter-

subjective alignment showing that disagreement was produced later than agree-

ment on all four levels of (non)-resonance (ß=304.52, SE =72.19, t=4.218, p<

.001). As for (non)-resonance itself, the following results were observed. Sig-

niﬁcantly slower turn transitions were found for elaborated responses compared

to formal resonance (ß=404.22, SE =117.25, z=3.448, p=.003) but not

compared to semantic resonance (ß=245.62, SE =122.27, z=2.009, p=.176),

which was produced slower than formal resonance. The diﬀerence between

formal and semantic resonance was not signiﬁcant (ß=158.61, SE =79.47,

z=1.996, p=.181). Moreover, response tokens were not produced signiﬁcantly

slower than formal resonance (ß=55.35, SE =65.76, z=0.842, p=.828) or

signiﬁcantly faster than semantic resonance (ß=–103.25, SE =75.97, z=

–1.359, p=.513). It should be noted that there was also a signiﬁcant diﬀerence

between the two types of non-resonance, response tokens and elaborated

responses (ß=348.87, SE =118.39, z=2.947, p=.016), which suggests

an eﬀect of response length, but this result is not particularly relevant for this

study. Table 2 summarizes the durations of turn transitions for the four types of

table 2. Predicted mean durations of turn transitions (in ms) for the four

types of (non)-resonance (formal, semantic, response tokens, and elaborated

responses) and the two types of intersubjective alignment (agreement and

disagreement) in the regression model (standard errors are in parentheses).

Agreement Disagreement

Resonance: Formal –109.31 (69.95) 195.21 (87.42)

Resonance: Semantic 49.30 (80.03) 353.84 (86.56)

Non-resonance: Response tokens –53.96 (56.49) 250.56 (88.82)

Non-resonance: Elaborated responses 294.91 (121.82) 599.43 (118.16)

660

˜ldvere et al.

Downloaded from https://www.cambridge.org/core. IP address: 193.157.111.124, on 06 Nov 2021 at 10:15:16, subject to the Cambridge Core

(non)-resonance and the two types of intersubjective alignment in the regression

model.

As can be seen in the table, agreements are consistently produced earlier than

disagreements (e.g., for formal resonance –109.31 ms and 195.21 ms, respec-

tively). In all cases, formal resonance is produced fastest, and elaborated

responses of non-resonance slowest, with semantic resonance and response

tokens of non-resonance in between. However, despite being expressed later

than agreement, the apparent ease with which the speakers expressed disagree-

ment through resonance is striking when compared with ﬁndings from previ-

ous research (see Section 7.2).

7. Discussion

This study examined the dialogic occurrence of resonance in stance-taking

turns in everyday face-to-face conversation. In order to gain a better under-

standing of the phenomenon, we approached it both from an intersubjective

and a cognitive perspective. The following sub-sections discuss the results

previously presented in the light of the study’s predictions.

7.1. the role of dialogic resonance in disagreement

Prediction 1 targeted the intersubjective motivations of resonance. It stated

that resonance is more likely to appear in disagreement than non-resonance,

which is more likely to be the case in agreement. The study provides full

support for this prediction. While this study is not the ﬁrst one to point this out

(e.g., Dori-Hacohen, 2017; Du Bois, 2014; Zima et al., 2009), there have been

no previous attempts at strict operationalization and statistical conﬁrmation of

the close relationship between resonance and disagreement. The result raises

the question of why resonance is more common in disagreement. It seems

reasonable to assume that, like other dispreferred responses, disagreement is a

face-threatening act that may change the preferred joint project initiated by the

ﬁrst speaker, i.e., to seek some sort of agreement, which means that the second

speaker must do extra work to plan and formulate an appropriate response

(Clark, 1996; see also Sacks, 1987, for the ‘preference for agreement’principle).

This is particularly important in everyday conversation where speakers typi-

cally are inclined to be cooperative and promote solidarity and aﬃliation

among themselves. Therefore, our interpretation of the corpus data is that

resonance helps speakers achieve the goal of countering the negative social

consequences associated with dispreferred responses. Consider examples

(7) and (8), taken from conversations among close family members in LLC–

2, where the stance-taking sequences are in bold.

661

resonance in dialogue

Downloaded from https://www.cambridge.org/core. IP address: 193.157.111.124, on 06 Nov 2021 at 10:15:16, subject to the Cambridge Core

(7) A: we’d have to be more careful we wouldn’t be able to go somewhere that

already was at the top of the hill

B: well the whole point of Blackheath is that it’s a huge fucking hill the station’s

at the top of the hill and if you’re saying you’re not gonna have a car

A: <vocal desc="sighs"/> the station isn’t that far up the hill

(8) A: I’m surprised that she’s unaware of the programme at seven AM on Sunday which

is called uh it’s called Sunday

B: well why should she be she hasn’t hitherto been particularly interested in

religious things [has she]

A: [you mean] she hasn’t particularly been up at seven AM

B: no that too

In both (7) and (8), the speakers have diﬀerent views on the topics being

discussed, but the disagreement is achieved by diﬀerent means. While speaker

B’s stance follow in (7) is only minimally coherent with A’s stance lead (the

only content word that links them is hill), the stance-taking sequence in

(8) displays structural parallelisms along multiple levels of linguistic represen-

tation (e.g., the stance adverb particularly, the negated and predicative con-

structions, but also co-reference (she) and, as revealed in the original audio ﬁle,

rise–fall intonation). In other words, speaker A in (8) seems to construe her

response in a way that foregrounds what is shared by the interlocutors rather

than where they diﬀer, which is the case in (7). Based on this, we propose that

the reason why resonance is often used in disagreement in our data of

impromptu speech is because the reuse of prior linguistic material at the lower

levels of lexical items, syntactic structure, semantics, and intonation reinforces

the perception of interpersonal solidarity at the higher level of social relations.

Resonance may thereby have the eﬀect of mitigating the force of the disagree-

ment and narrowing the conceptual gap between the interlocutors through

such linguistic parallels. By hearing their own words and ideas back, speakers

may feel reassured about the interlocutor’s engagement with their beliefs and

attitudes, and therefore they are not so easily oﬀended even though these

beliefs and attitudes are actually being contested. This is in line with Nir

(2017), who argues that resonance evokes a sense of aﬃnity and coherence,

while non-resonance creates “a distancing eﬀect”(2017, p. 117), both at the

lower level of linguistic material and at the higher level of social rapport

(cf. Dori-Hacohen, 2017).

An alternative interpretation of the occurrence of resonance in disagreement

can be found in Heritage and Raymond’s(2005) framework of epistemic

authority. According to them, speakers are sensitive to who has primary

epistemic rights to claims, and one way in which second speakers make claims

to those rights is by repeating what the ﬁrst speaker said (see also Stivers, 2005).

Research on such epistemic independence from the second speaker has almost

exclusively focused on agreements, and it has been taken for granted that the

results will generalize to disagreements too. However, we are hesitant to

662

˜ldvere et al.

Downloaded from https://www.cambridge.org/core. IP address: 193.157.111.124, on 06 Nov 2021 at 10:15:16, subject to the Cambridge Core

interpret our results in the light of this generalization because of the fact that

there are fundamental functional and social diﬀerences between agreement and

disagreement. Vatanen (2018), for instance, notes that “in disagreements, the

question is more about how things should be thought of in the ﬁrst place rather

than about whose (similar) knowledge is primary”(2018, p. 113). In (8) above,

the question is not about epistemic independence but rather about setting the

record straight on a debatable issue (a third person’s reason for not knowing a

radio programme). Moreover, disagreements by default convey epistemic

independence from the interlocutor’s claims because the claims are not the

same, or similar, to start with. Finally, this alternative interpretation would not

explain the diﬀerence in the occurrence of resonance in disagreement com-

pared to agreement in this study. This said, future research should aim to

conﬁrm the interpretation of the mitigating function of resonance under more

strict experimental conditions in order to be able to validate the arguments that

we made based on frequency in LLC–2.

7.2. the role of cognitive facilitation in resonance

production

Prediction 2 targeted the role of cognitive facilitation in resonance, which we

tested based on strictly controlled measurements of durations of turn tran-

sitions in the conversations. We made a distinction between two types of

resonance (formal and semantic) and two types of non-resonance (response

tokens and elaborated responses), and predicted that turn transitions are

fastest for response tokens, followed by formal and semantic resonance,

and elaborated responses, in that order. Thus, with the exception of response

tokens, which are short and highly frequent, we expected resonance to be

produced faster than non-resonance due to the facilitating eﬀect of reusing

prior linguistic material. In the statistical model presented in Section 6 above,

we tested this prediction together with the open question of whether or not

there are diﬀerences in timing between agreement and disagreement. The

results provided a positive answer to this question, showing that disagree-

ment was expressed later than agreement (cf. Meyer et al., 2018;Roberts

et al., 2015; Stivers et al., 2009), and that this eﬀect was independent of

whether they included resonance or not. However, there were diﬀerences in

the amount of time that the speakers took to express those views. Speciﬁcally,

we found signiﬁcantly faster turn transitions for formal resonance compared

to elaborated responses of non-resonance. The non-signiﬁcant association

between elaborated responses and the other type of resonance –semantic –

may have been because of the greater variation of form in semantic resonance,

which reduces the degree to which speakers can access and quickly reproduce

prior linguistic material.

663

resonance in dialogue

Downloaded from https://www.cambridge.org/core. IP address: 193.157.111.124, on 06 Nov 2021 at 10:15:16, subject to the Cambridge Core

However, when compared with ﬁndings from previous research, the pre-

dicted mean durations in this study are small for both types of resonance and

for both types of intersubjective alignment (cf. Table 2 above). We would

especially like to draw the reader’s attention to the apparent ease with which the

speakers expressed disagreement through resonance, based on the observation

made in Section 7.1 above that resonance is common in disagreement situa-

tions. Speciﬁcally, it took the speakers less than 200 ms (M=195.21 ms) to

disagree with each other via formal resonance (e.g., it was boring !it wasn’t

that boring) and 353.84 ms to do so through semantic resonance. This is very

fast considering that it took them on average 250.56 ms to produce a single

response token such as no, and that the nearly 600 ms (M=599.43 ms) recorded

for elaborated responses comes close to the temporal threshold of 700–800 ms

after which a dispreferred response is imminent (Kendrick & Torreira, 2015).

Moreover, only elaborated responses come close to the mean latencies observed

in Meyer et al. (2018), where long negative responses to polar questions were

given as late as c. 700 ms (depending on the experimental condition). Examples

(7) and (8) above illustrate the diﬀerence between the timing of elaborated

responses of non-resonance and semantic resonance, respectively. While the

stance follow in (7) is produced after a noticeable gap of 431 ms, the stance

follow in (8) occurs in slight overlap with the prior turn.

Based on the assumed relationship between faster turn transitions on the one

hand and greater cognitive accessibility of previously mentioned words and

structures on the other hand (cf. Ariel, 1988; Tachihara & Goldberg, 2020; see

Prediction 2), the fast turn transitions observed for resonance in both agree-

ment and disagreement situations provide empirical evidence in support of the

view that cognitive facilitation plays an important role in resonance produc-

tion. Speciﬁcally, it gives the speakers the necessary means to counter the

temporal challenges of impromptu speech. Similarly, Du Bois et al. (2014)

view cognitive facilitation and syntactic and lexical priming as a distinct phase

in the larger resonance cycle that creates conditions for the uptake of certain

linguistic constructions. This is, however, not where the resonance cycle ends.

We know that speakers do not simply blurt out words without any consider-

ation for the interpersonal eﬀects that their words may have. Dispreferred

responses given too early are especially risky because they defy social expec-

tations (see, e.g., Bögels et al., 2015, on the processing cost of no after a short

gap compared to a long gap). To mitigate these risks, speakers make use of

various qualiﬁcation devices such as turn-initial in-breaths, particles, and

hedges, which delay the onset of the base dispreferred response (Kendrick &

[6] As indicated in Table 1 in Section 5.2 above, prosodic units were considered to be an

important criterion for determining utterance boundaries. Since the tag question in

(8) belongs to the larger prosodic unit, the measurement was taken after the tag question.

664

˜ldvere et al.

Downloaded from https://www.cambridge.org/core. IP address: 193.157.111.124, on 06 Nov 2021 at 10:15:16, subject to the Cambridge Core

Torreira, 2015). In fact, almost half of all the elaborated responses in our data

are qualiﬁed in such a way, while only 11% of the resonating stance-taking

sequences are. Yet, the latter are still produced at a noticeably greater speed

than the former.

The conclusion we draw based on the results above is that intersubjective

motivations and cognitive facilitation provide diﬀerent, yet complementary,

aﬀordances for the occurrence of resonance in dialogue. The fast turn transi-

tions observed for disagreement, in particular, seem to indicate that, while

cognitive facilitation gives speakers the means to provide a swift response, it is

the mitigating function of resonance that allows them to respond swiftly in

disagreement situations. In this way, resonance performs a similar function to,

say, turn-initial hedges, allowing the speakers to avoid a long gap. The absence

of resonance (or turn-initial hedges) creates further distance between the

interlocutors, reﬂected in their resistance to provide a swift response. There-

fore, the combined data suggest that cognitive facilitation goes hand in hand

with the strategic and appropriate formulation of one’s personal beliefs and

attitudes, and the achievement of interpersonal engagement between the

interlocutors. We agree with Du Bois et al. (2014) that the activation of

linguistic material in the prior discourse constitutes only one phase of the

larger resonance cycle, and that it is the subsequent uptake and selective

reproduction of the material that completes the cycle and gives life to dialogic

resonance with all its ancillary social consequences. Based on this, it is possible

to say that dialogic resonance in particular and linguistic coordination in

general do not lie in the privileged role of any one process, either communi-

cative or cognitive, but in the close interplay between intersubjective motiva-

tions and cognitive facilitation. As stated in Section 7.1 above, there is a need to

conﬁrm the mitigating function of resonance in a laboratory setting. The same

is true of the role of cognitive facilitation. The present study examined

properties that were expected to correlate with cognitive facilitation such as

the timing of turns in conversation (see also Roberts et al., 2015), but future

research should aim to extract more direct online measures of cognitive facil-

itation and priming in order to uncover the exact nature of interactive priming

(Garrod & Pickering, 2004) in Du Bois’resonance cycle.

8. Conclusion

Natural conversation is highly coordinated and draws simultaneously on the

social goals that speakers have in dialogue and the cognitive aspects that

underpin it. This study demonstrates this empirically by focusing on a com-

pelling type of coordination, namely resonance in stance-taking turns in

everyday face-to-face conversation in LLC–2. The corpus analysis was carried

out in two parts. At the core of the ﬁrst part of the analysis were the

665

resonance in dialogue

Downloaded from https://www.cambridge.org/core. IP address: 193.157.111.124, on 06 Nov 2021 at 10:15:16, subject to the Cambridge Core

intersubjective motivations of resonance and the question of whether reso-

nance is more likely than non-resonance to appear in disagreement than

agreement, and, if so, why this may be the case. The results provided a positive

answer to this question. Arguably, this is due to the cooperative nature of

everyday conversation and the important role that resonance plays in mitigat-

ing the force of the ensuing disagreement through parallels along multiple

levels of linguistic representation. In the second part of the analysis, we

investigated the role of cognitive facilitation in resonance production. The

results showed that utterances that included formal resonance were produced

faster than utterances constructed from scratch. We interpret this as an indi-

cation that formal resonance has a facilitating eﬀect on turn uptake, prompted

by the activation of the same linguistic representations in the mind of the

second speaker by the prior speaker’s turn. We also found that disagreement

was expressed later than agreement; however, the resonating sequences expres-

sing disagreement were still produced strikingly fast. Taken together, then, the

results point to the close and reciprocal relationship between communicative

and cognitive aspects of resonance whereby the face-saving intersubjective

motivation of resonance combines with its facilitating cognitive eﬀect to

promote appeasing communication.

references

Allen, M. L., Haywood, S., Rajendran, G. & Branigan, H. (2011). Evidence for syntactic

alignment in children with autism. Developmental Science 14(3), 540–548.

Ariel, M. (1988). Referring and accessibility. Journal of Linguistics 24(1), 65–87.

Atkinson, J. M. & Heritage, J. (1984). Preference organization. In J. M. Atkinson & J. Heritage

(eds), Structures of social action: studies in Conversation Analysis (pp. 53–56). Cambridge:

Cambridge University Press.

Barthel, M., Sauppe, S., Levinson, S. C. & Meyer, A. S. (2016). The timing of utterance

planning in task-oriented dialogue: evidence from a novel list-completion paradigm. Frontiers

in Psychology 7,1–13.

Bates, D., Mächler, M., Bolker, B. M. & Walker, S. (2015). Fitting linear mixed-eﬀects models

using lme4. Journal of Statistical Software 67(1), 1–48.

Boersma, P. (2001). Praat: a system for doing phonetics by computer. Glot International 5(9/10),

341–345.

Bögels, S., Kendrick, K. & Levinson, S. C. (2015). Never say no …How the brain interprets the

pregnant pause in conversation. PLoS One 10,1–15.

Brennan, S. E. & Clark, H. H. (1996). Conceptual pacts and lexical choice in conversation.

Journal of Experimental Psychology: Learning, Memory, and Cognition 22(6), 1482–1493.

Brône, G. & Zima, E. (2014). Towards a dialogic construction grammar: ad hoc routines and

resonance activation. Cognitive Linguistics 25(3), 457–495.

Chafe, W. & Nichols, J. (1986). Evidentiality: the linguistic coding of epistemology. Norwood, NJ:

Ablex.

Clark, H. H. (1996). Using language. Cambridge: Cambridge University Press.

Dideriksen, C., Fusaroli, R., Tylén, K., Dingemanse, M. & Christiansen, M. H. (2019).

Contextualizing conversational strategies: backchannel, repair and linguistic alignment in

spontaneous and task-oriented conversations. In A. K. Goel, C. M. Seifert & C. Freksa (eds),

666

˜ldvere et al.

Downloaded from https://www.cambridge.org/core. IP address: 193.157.111.124, on 06 Nov 2021 at 10:15:16, subject to the Cambridge Core

Proceedings of the 41st Annual Conference of the Cognitive Science Society (pp. 261–267).

Cognitive Science Society.

Dori-Hacohen, G. (2017). Creative resonance and misalignment stance: achieving distance in

one Hebrew interaction. Functions of Language 24(1), 16–40.

Du Bois, J. W. (2007). The stance triangle. In R. Englebretson (ed.), Stancetaking in discourse:

subjectivity, evaluation, interaction (pp. 139–182). Amsterdam: John Benjamins.

Du Bois, J. W. (2010). Towards a dialogic syntax [Unpublished manuscript]. Department of

Linguistics, University of California, Santa Barbara, USA.

Du Bois, J. W. (2014). Towards a dialogic syntax. Cognitive Linguistics 25(3), 359–410.

Du Bois, J. W. & Giora, R. (2014). From cognitive-functional linguistics to dialogic syntax.

Cognitive Linguistics 25(3), 351–357.

Du Bois, J. W., Hobson, R. P. & Hobson, J. A. (2014). Dialogic resonance and intersubjective

engagement in autism. Cognitive Linguistics 25(3), 411–441.

Du Bois, J. W., Schuetze-Coburn, S., Cumming, S. & Paolino, D. (1993). Outline of discourse

transcription. In J. A. Edwards & M. D. Lampert (eds), Talking data: transcription and coding

in discourse research (pp. 45–89). New York: Erlbaum.

Fuoli, M. (2017). Building a trustworthy corporate identity: a corpus-based analysis of stance in

annual and corporate social responsibility reports. Applied Linguistics,39(6), 846–885.

Fusaroli, R., Bahrami, B., Olsen, K., Roepstorﬀ, A., Rees, G., Frith, C. & Tylén, K. (2012).

Coming to terms: quantifying the beneﬁts of linguistic coordination. Psychological Science 23

(8), 931–939.

Fusaroli, R. & Tylén, K. (2012). Carving language for social coordination: a dynamical

approach. Interaction Studies 13(1), 103–124.

Garrod, S. & Pickering, M. J. (2004). Why is conversation so easy? TRENDS in Cognitive

Sciences 8(1), 8–11.

Garrod, S. & Pickering, M. J. (2015). The use of content and timing to predict turn transitions.

Frontiers in Psychology 6,1–12.

Heldner, M. & Edlund, J. (2010). Pauses, gaps and overlaps in conversation. Journal of Phonetics

38, 555–568.

Heritage, J. & Raymond, G. (2005). The terms of agreement: indexing epistemic authority and

subordination in talk-in-interaction. Social Psychology Quarterly 68(1), 15–38.

Holler, J. & Kendrick, K. H. (2015). Unaddressed participants’gaze in multi-person interac-

tion: optimizing recipiency. Frontiers in Psychology 6,1–14.

Holler, J., Kendrick, K. H. & Levinson, S. C. (2017). Processing language in face-to-face

conversation: questions with gestures get faster responses. Psychonomic Bulletin & Review 25

(5), 1900–1908.

Hothorn, T., Bretz, F. & Westfall, P. (2008). Simultaneous inference in general parametric

models. Biomedical Journal 50(3), 346–363.

Hunston, S. & Thompson, G. (2000). Evaluation in text: authorial stance and the construction of

discourse. Oxford: Oxford University Press.

Kendrick, K. H. & Torreira, F. (2015). The timing and construction of preference: a quanti-

tative study. Discourse Processes 52(4), 255–289.

Landis, J. & Koch, G. (1977). The measurement of observer agreement for categorical data.

Biometrics 33(1), 159–174.

Lerner, G. H. (2002). Turn-sharing: the choral co-production of talk in interaction. In C. Ford,

B. Fox & S. Thompson (eds), The language of turn and sequence (pp. 225–256). Oxford: Oxford

University Press.

Levelt, W. J. M., Roelofs, A. & Meyer, A. S. (1999). A theory of lexical access in speech

production. Behavioral and Brain Sciences 22(1), 1–75.

Levinson, S. C. & Torreira, F. (2015). Timing in turn-taking and its implications for processing

models of language. Frontiers in Psychology 6,1–17.

Linell, P. (2009). Rethinking language, mind, and world dialogically: interactional and contextual

theories of human sense-making. Charlotte, NC: Information Age Publishing.

Marín-Arrese, J. I. (2015). Epistemic legitimisation and inter/subjectivity in the discourse of

parliamentary and public inquiries. Critical Discourse Studies 12(3), 261–278.

667

resonance in dialogue

Downloaded from https://www.cambridge.org/core. IP address: 193.157.111.124, on 06 Nov 2021 at 10:15:16, subject to the Cambridge Core

Martin, J. & White, P. (2005). The language of evaluation: appraisal in English. London:

Palgrave Macmillan.

Maschler, Y. & Nir, B. (2014). Complementation in linear and dialogic syntax: the case of

Hebrew divergently aligned discourse. Cognitive Linguistics 25(3), 523–557.

Meyer, A. S., Alday, P. M., Decuyper, C. & Knudsen, B. (2018). Working together: contri-

butions of corpus analyses and experimental psycholinguistics to understanding conversa-

tion. Frontiers in Psychology 9,1–13.

Müller, F. E. (1996). Aﬃliating and disaﬃliating with continuers: prosodic aspects of reci-

piency. In E. Couper-Kuhlen & M. Selting (eds), Prosody in conversation (pp. 131–176).

Cambridge: Cambridge University Press.

Nir, B. (2017). Resonance as a resource for stance-taking in narratives. Functions of Language 24

(1), 94–120.

Nir, B., Dori-Hacohen, G. & Maschler, Y. (2014). Formulations on Israeli political talk radio:

from actions and sequences to stance via dialogic resonance. Discourse Studies 16(4), 534–571.

Nir, B. & Zima, E. (2017). Stance-taking, dialogic resonance and the construction of intersub-

jectivity. Functions of Language 24(1), 3–15.

O’Keeﬀe, A. & Adolphs, S. (2008). Response tokens in British and Irish discourse: corpus,

context and variational pragmatics. In K. P. Schneider & A. Barron (eds), Variational

pragmatics: a focus on regional varieties in pluricentric languages (pp. 69–98). Amsterdam:

John Benjamins.

Palmer, F. (2001). Mood and modality (2nd ed.). Cambridge: Cambridge University Press.

Paradis, C. & Willners, C. (2011). Antonymy: from conventionalization to meaning-making.

Review of Cognitive Linguistics 9(2), 367–391.

Pickering, M. J. & Garrod, S. (2004). Toward a mechanistic psychology of dialogue. Behavioral

and Brain Sciences 27(2), 169–225.

Pickering, M. J. & Garrod, S. (2005). Establishing and using routines during dialogue:

implications for psychology and linguistics. In A. Cutler (ed.), Twenty-ﬁrst century psycho-

linguistics: four cornerstones (pp. 85–101). Mahwah, NJ: Erlbaum.

Pomerantz, A. (1984). Agreeing and disagreeing with assessments: some features of preferred/

dispreferred turn shapes. In J. M. Atkinson & J. Heritage (eds), Structures of social action:

studies in Conversation Analysis (pp. 57–101). Cambridge: Cambridge University Press.

Põldvere, N., Frid, J., Johansson, V. & Paradis, C. (2021). Challenges of releasing audio

material for spoken data: the case of the London–Lund Corpus 2. Research in Corpus

Linguistics 9(1), 35–62.

Põldvere, N., Fuoli, M. & Paradis, C. (2016). A study of dialogic expansion and contraction in

spoken discourse using corpus and experimental techniques. Corpora 11(2), 191–225.

Põldvere, N., Johansson, V. & Paradis, C. (in press). On the London–Lund Corpus 2: design,

challenges and innovations. English Language and Linguistics 25(3).

Põldvere, N. & Paradis, C. (2019). Motivations and mechanisms for the development of the

reactive what-x construction in spoken dialogue. Journal of Pragmatics 143,65–84.

Põldvere, N. & Paradis, C. (2020). ‘What and then a little robot brings it to you?’The reactive

what-x construction in spoken dialogue. English Language and Linguistics 24(2), 307–332.

Rasenberg, M., Özyürek, A. & Dingemanse, M. (2020). Alignment in multimodal interaction:

an integrative framework. Cognitive Science 44,1–29.

R Core Team. (2014). R: a language and environment for statistical computing. R Foundation for

Statistical Computing. Online <https://www.r-project.org>.

Roberts, S. G., Torreira, F. & Levinson, S. C. (2015). The eﬀects of processing and sequence

organization on the timing of turn taking: a corpus study. Frontiers in Psychology 6,1–16.

Robinson, J. D. (2020). Revisiting preference organization in context: a qualitative and quan-

titative examination of responses to information seeking. Research on Language and Social

Interaction 53(2), 197–222.

Sacks, H. (1987). On the preference for agreement and contiguity in sequences in conversation.

In G. B. Button & J. R. E. Lee (eds), Talk and social organisation (pp. 54–69). Clevedon:

Multilingual Matters.

668

˜ldvere et al.

Downloaded from https://www.cambridge.org/core. IP address: 193.157.111.124, on 06 Nov 2021 at 10:15:16, subject to the Cambridge Core

Sacks, H., Schegloﬀ,E.A.&Jeﬀerson, G. (1974). A simplest systematics for the organization of

turn-taking for conversation. Language 50(4), 696–735.

Schegloﬀ, E. A. (1988). On an actual virtual servo-mechanism for guessing bad news: a single

case conjecture. Social Problems 35(4), 442–457.

Simaki, V., Skeppstedt, M., Paradis, C., Kerren, A. & Sahlgren, M. (2017). Annotating speaker

stance in discourse: the Brexit Blog Corpus. Corpus Linguistics and Linguistic Theory 16(2),

215–248.

Stivers, T. (2005). Modiﬁed repeats: one method for asserting primary rights from second

position. Research on Language and Social Interaction 38(2), 131–158.

Stivers, T. & Enﬁeld, N. J. (2010). A coding scheme for question–response sequences in

conversation. Journal of Pragmatics 42(10), 2620–2626.

Stivers, T., Enﬁeld, N. J., Brown, P., Englert, C., Hayashi, M., Heinemann, T., Hoymann, G.,

Rossano, F., de Ruiter, J. P., Yoon, K.-E. & Levinson, S. C. (2009). Universals and cultural

variation in turn-taking in conversation. Proceedings of the National Academy of Sciences of the

United States of America 106(26), 10587–10592.

Tachihara, K. & Goldberg, A. E. (2020). Cognitive accessibility predicts word order of couples’

names in English and Japanese. Cognitive Linguistics 31(2), 231–249.

van de Weijer, J., Paradis, C., Willners, C. & Lindgren, M. (2014). Antonym canonicity:

temporal and contextual manipulations. Brain and Language 128(1), 1–18.

Vatanen, A. (2018). Responding in early overlap: recognitional onsets in assertion sequences.

Research on Language and Social Interaction 51(2), 107–126.

Wittenburg, P., Brugman, H., Russel, A., Klassmann, A. & Sloetjes, H. (2006). ELAN: a

professional framework for multimodality research. In N. Calzolari, K. Choukri, A. Gang-

emi, B. Maegaard, J. Mariani, J. Odijk & D. Tapias (eds), Proceedings of the 5th International

Conference on Language Resources and Evaluation (pp. 1556–1559). ELRA.

Zima, E., Brône, G., Feyaerts, K. & Sambre, P. (2009). “Ce n’est pas très beau ce que vous avez

dit!”The activation of resonance in French parliamentary debates. Discours 4,1–17.

669

resonance in dialogue

Downloaded from https://www.cambridge.org/core. IP address: 193.157.111.124, on 06 Nov 2021 at 10:15:16, subject to the Cambridge Core

Feedback quality and divided attention: exploring commentaries on alignment in task-oriented dialogue

Article

Full-text available

Dec 2023

While studies have shown the importance of listener feedback in dialogue, we still know little about the factors that impact its quality. Feedback can either indicate that the addressee is aligning with the speaker (i.e. “positive” feedback) or that there is some communicative trouble (i.e. “negative” feedback). This study provides an in-depth account of listener feedback in task-oriented dialogue (a director-matcher game), where positive and negative feedback is produced, thus expressing both alignment and misalignment. By manipulating the listener’s cognitive load through a secondary mental task, we measure the effect of divided attention on the quantity and quality of feedback. Our quantitative analysis shows that performance and feedback quantity remain stable across cognitive load conditions, but that the timing and novelty of feedback vary: turns are produced after longer pauses when attention is divided between two speech-focused tasks, and they are more economical (i.e. include more other-repetitions) when unrelated words need to be retained in memory. These findings confirm that cognitive load impacts the quality of listener feedback. Finally, we found that positive feedback is more often generic and shorter than negative feedback, and that its proportion increases over time.

British Conversation is Changing: Resonance and Engagement in the BNC1994 and the BNC2014

Article

Full-text available

Jun 2024
APPL LINGUIST

This applied study assesses the degree to which speakers re-use and acknowledge parts of one another's utterances. This form of alignment is called resonance (DuBois 2014; Tantucci and Wang 2021), and is a decisive indicator of creativity and verbal engagement. Consistent absence of resonance indicates interactional detachment, which is distinctive of autistic speech (Tantucci and Wang 2023). We analysed resonance in naturalistic interaction among British speakers in the demographically sampled sections of the British National Corpora of English: the BNC1994 and the BNC2014. We controlled for creativity, age, class, gender, context , dialect, and intra-generational speech for 1,600 turns of informal speech. We discovered that upper-class people from the corporate world and neighbouring sectors mutually resonated much more in 2014 than they used to in 1994. This may be due to the dramatic change in corporate and institutional communication in the 2000s, involving a new turn towards corporate social responsibility, participatory frameworks in higher education, and the enactment of ideologies such as inclusivity, engagement, and equality in higher social grades of British society. This plausibly affected not only the system of values of those communities but also their inter-actional behaviour, now increasingly geared towards overt acknowledgement of other people's talk.

Speakers align both their gestures and words not only to establish but also to maintain reference to create shared labels for novel objects in interaction

Conference Paper

Full-text available

May 2024

When we communicate with others, we often repeat aspects of each other's communicative behavior such as sentence structures and words. Such behavioral alignment has been mostly studied for speech or text. Yet, language use is mostly multi-modal, flexibly using speech and gestures to convey messages. Here, we explore the use of alignment in speech (words) and co-speech gestures (iconic gestures) in a referential communication task aimed at finding labels for novel objects in interaction. In particular, we investigate how people flexibly use lexical and gestural alignment to create shared labels for novel objects and whether alignment in speech and gesture are related over time. The present study shows that interlocutors establish shared labels multimodally, and alignment in words and iconic gestures are used throughout the interaction. We also show that the amount of lexical alignment positively associates with the amount of gestural alignment over time, suggesting a close relationship between alignment in the vocal and manual modalities.

Ah oui d’accord okay : marqueurs discursifs et expression de l’alignement conversationnel

Article

Full-text available

Jun 2024

Tout dialogue nécessite une certaine coordination afin d’assurer la réussite de la tâche: les représentations mentales des interlocuteurs doivent être négociées et converger progressivement au cours de l’interaction. Ce processus est appelé alignement conversationnel par Pickering et Garrod (2021). Parmi les outils disponibles pour exprimer l’alignement conversationnel, cet article se penche sur les marqueurs discursifs d’alignement (MDAs). Notre étude quantitative en dresse le portrait et la distribution dans des dialogues orientés-tâche. L’analyse a révélé que ces marqueurs prennent une place de plus en plus proéminente dans le dialogue à mesure que les représentations des interlocuteurs sont partagées et consolidées, acquérant ainsi un rôle structurel en plus de leur valeur interpersonnelle de base. Certains marqueurs tendent à se spécialiser dans une (ou deux) fonction particulière, et les locuteurs exploitent ces ressources en combinant parfois les formes et les fonctions dans d’impressionnants empilements de marqueurs. Certaines formes semblent assez spécifiques au dialogue orienté-tâche et moins prototypiques en tant que marqueurs discursifs, comme ça marche ou j’ai, mais elles remplissent les critères définitoires et ont la même valeur pragmatique que d’autres formes plus classiques comme OK.

On the London-Lund Corpus 2: Design, challenges and innovations

Article

Full-text available

Sep 2021
Engl Lang Ling

This article describes and critically examines the challenging task of compiling The London-Lund Corpus 2 (LLC-2) from start to end, accounting for the methodological decisions made in each stage and highlighting the innovations. LLC-2 is a half-a-million-word corpus of contemporary spoken British English with recordings from 2014 to 2019. Its size and design are the same as those of the world's first machine-readable spoken corpus, The London-Lund Corpus of Spoken English with data from the 1950s to 1980s. In this way, LLC-2 allows not only for synchronic investigations of contemporary speech but also for principled diachronic research of spoken language across time. Each stage of the compilation of LLC-2 posed its own challenges, ranging from the design of the corpus, the recruitment of the speakers, transcription, markup and annotation procedures, to the release of the corpus to the international research community. The decisions and solutions represent state-of-the-art practices of spoken corpus compilation with important innovations that enhance the value of LLC-2 for spoken corpus research, such as the availability of both the transcriptions and the corresponding time-aligned audio files in a standard compliant format.

Special issue on spoken language in time and across time: Introduction

Article

Full-text available

Jul 2021

The idea of this special issue on Spoken language in time and across time emerged at an international symposium on this topic that we organised at Lund University on 20 September 2019. The purpose of the symposium was to celebrate important past and present achievements of spoken language research as well as past and present corpora available for such research. Some speakers reported on academic and technical advances from the past, while others offered information about state-of-the-art research on spoken language and spoken corpus compilation. Our idea with the symposium was also to bring together early career scholars, somewhat more senior scholars as well as senior scholars – the latter actually active when interest in spoken language and spoken corpus compilation was in its infancy. The type of spoken corpora in focus extended from the world's first publicly available, machine-readable spoken corpus, The London–Lund Corpus of Spoken English (Svartvik 1990), nowadays referred to as LLC–1, through to the spoken parts of The British National Corpora (BNC) from 1994 (BNC Consortium 2007) and 2014 (Love et al. 2017), The Diachronic Corpus of Present-Day Spoken English (DCPSE) consisting of LLC–1 and the British component of The International Corpus of English (ICE–GB), Santa Barbara Corpus of Spoken American English (SBCSAE) (Du Bois et al. 2000–5), The Corpus of Contemporary American English (COCA) (Davies 2008–) and finally the most recent one, The London–Lund Corpus 2 (LLC–2) (Põldvere, Johansson & Paradis 2021a). The symposium thus covered approximately half a century of data from publicly available corpora compiled for multipurpose use by the academic community for research on spoken English in different contexts.

Challenges of releasing audio material for spoken data: The case of the London-Lund Corpus 2

Article

Full-text available

Jul 2021

This article aims to describe key challenges of preparing and releasing audio material for spoken data and to propose solutions to these challenges. We draw on our experience of compiling the new London-Lund Corpus 2 (LLC-2), where transcripts are released together with the audio files. However, making the audio material publicly available required careful consideration of how to, most effectively, 1) align the transcripts with the audio and 2) anonymise personal information in the recordings. First, audio-to-text alignment was solved through the insertion of timestamps in front of speaker turns in the transcription stage, which, as we show in the article, may later be used as a valuable complement to more robust automatic segmentation. Second, anonymisation was done by means of a Praat script, which replaced all personal information with a sound that made the lexical information incomprehensible but retained the prosodic characteristics. The public release of the LLC-2 audio material is a valuable feature of the corpus that allows users to extend the corpus data relative to their own research interests and, thus, broaden the scope of corpus linguistics. To illustrate this, we present three studies that have successfully used the LLC-2 audio material.

On the London-Lund Corpus 2: Design, challenges and innovations

Article

Full-text available

Sep 2021
Engl Lang Ling

Challenges of releasing audio material for spoken data: The case of the London-Lund Corpus 2

Article

Full-text available

Jul 2021

Building a Trustworthy Corporate Identity: A Corpus-Based Analysis of Stance in Annual and Corporate Social Responsibility Reports

Article

Full-text available

Dec 2018

Matteo Fuoli

This article presents a corpus-based analysis of stance in annual and corporate social responsibility (CSR) reports. It investigates how companies use stance expressions to construct and promote a positive corporate identity to gain the trust of the stakeholder groups that these texts target. The results show that companies profile distinct identities in annual and CSR reports. In annual reports, they use stance resources to portray themselves as unbiased, rational, and competent decision makers. In CSR reports, they present themselves as committed, honest, and caring corporate citizens. These discursive identities are interpreted as strategic self-representations that optimize the persuasive appeal of the reports by addressing the specific expectations of the target readerships. This study sheds some new light on the identity work performed by companies in their public discourse. It also provides novel insights into the impression management strategies used by companies in annual and CSR reports. Finally, it provides both linguists and business communication scholars with a robust descriptive basis for critically assessing financial and CSR reporting.

Alignment in Multimodal Interaction: An Integrative Framework

Article

Full-text available

Nov 2020

When people are engaged in social interaction, they can repeat aspects of each other's communicative behavior, such as words or gestures. This kind of behavioral alignment has been studied across a wide range of disciplines and has been accounted for by diverging theories. In this paper, we review various operationalizations of lexical and gestural alignment. We reveal that scholars have fundamentally different takes on when and how behavior is considered to be aligned, which makes it difficult to compare findings and draw uniform conclusions. Furthermore, we show that scholars tend to focus on one particular dimension of alignment (traditionally, whether two instances of behavior overlap in form), while other dimensions remain understudied. This hampers theory testing and building, which requires a well-defined account of the factors that are central to or might enhance alignment. To capture the complex nature of alignment, we identify five key dimensions to formalize the relationship between any pair of behavior: time, sequence, meaning, form, and modality. We show how assumptions regarding the underlying mechanism of alignment (placed along the continuum of priming vs. grounding) pattern together with operationalizations in terms of the five dimensions. This integrative framework can help researchers in the field of alignment and related phenomena (including behavior matching, mimicry, entrainment, and accommodation) to formulate their hypotheses and operationalizations in a more transparent and systematic Correspondence should be sent to Marlou Rasenberg, This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. manner. The framework also enables us to discover unexplored research avenues and derive new hypotheses regarding alignment.

'What and then a little robot brings it to you?' The reactive what-x construction in spoken dialogue

Article

Full-text available

Jun 2020

In the process of compiling a new corpus of contemporary spoken British English, the London-Lund Corpus 2, we hit upon a construction used in the conversations recorded that had not previously been dealt with in the literature, namely the reactive what-x construction. Prompted by this discovery, we carried out a detailed analysis of its properties and constraints within the broad framework of Cognitive Linguistics, namely Construction Grammar, and found that the reactive what-x construction features the interrogative what directly followed by a phrasal or clausal complement x. Moreover, what forms one tone unit with the complement and never carries a nuclear pitch accent. The core meaning is to signal an immediate reaction to something said by another speaker in the preceding turn, and the dialogic functions include questions proper as well as expressions of disagreement. The two contributions of this study are: (i) to provide a definition of the reactive what-x construction and (ii) to propose a crucial theoretical extension of Construction Grammar involving a broadening of the concept of construction to cover not only the lexical-semantic pairing but also prosodic properties and the role of the construction in the interactive dialogic space in speech.

Evaluation in Text: Authorial Stance and the Construction of Discourse

Article

Feb 2000

This is an accessible and wide-ranging account of current research in one of the most central aspects of discourse analsysis: evalution in and of written and spoken language. Evalution is the broad cover term for the expression of a speakers - or writers - attitudes, feelings, and values. It covers areas sometimes referred to as stance, modality, affect or appraisal. Evaluation (a) expresses the speakers opinion and thus reflects the value-system of that person and their community; (b) constructs relations between speaker and hearer (or writer and reader); (c) plays a key role in how discourse is organized. Every act of evalution expresses and contributes to a communal value-system, which in turn is a component of the ideology that lies behind every written or spoken text. Conceptually, evaluation is comparative, subjective, and value-laden. In linguistic terms it may be analysed lexically, grammatically, and textually. These themes and perspectives are richly exemplified in the chapters of this book, by authors aware and observant of the fact that processes of linguistic analysis are themselves inherently evaluative. The editors open the book by introducing the field and provide separate, contextual introductions to each chapter. They have also collated the references into one list, itself a valuable research guide. The exemplary perspectives and analyses presented by the authors will be of central interest to everyone concerned with the analysis of discourse, whether as students of language, literature, or communication. They also have much to offer students of politics and culture. The editors open the book by introducing the field and provide separate, contextual introductions to each chapter. They have also collated the references into one list, itself a valuable research guide. The exemplary perspectives and analyses presented by the authors will be of central interest to everyone concerned with the analysis of discourse, whether as students of language, literature, or communication. They also have much to offer students of politics and culture.

2 On the Preferences for Agreement and Contiguity in Sequences in Conversation

Chapter

Dec 1987

Harvey Sacks

Mood and Modality

Book

Apr 2001

F. R. Palmer

Since the publication of F. R. Palmer's first edition of Mood and Modality in 1986, when the topic of 'modality' was fairly unfamiliar, there has been considerable interest in the subject as well as in grammatical typology in general. Modality is concerned with mood (subjunctive etc.) and with modal markers such as English modal verbs (can, may, must etc.) and is treated as a single grammatical category found in most of the languages of the world. In his investigation of this category, Palmer draws on a wealth of examples from a wide variety of languages. He discusses in detail familiar features in a number of mainly European languages, and also looks at less familiar features including 'evidential' systems and the contrast of realis/irrealis, both to be found in unrelated languages.

Revisiting Preference Organization in Context: A Qualitative and Quantitative Examination of Responses to Information Seeking

Article

Apr 2020

Jeffrey D Robinson

Quantitative studies applying conversation analysis to the study of the timing of answers to sequence-initiating actions expose anomalies in terms of what is known about preference organization. After briefly describing preference organization, anomalies in answer-timing research, and one explanation for such anomalies, this article presents one qualitative and one quantitative study of responses to one thickly contextualized action: positively formatted polar interrogatives implementing information seeking with a relatively ‘unknowing’ stance. Data include 249 questions gathered from videotapes of unstructured conversations. Qualitative results suggest that, rather than two basic answer types (i.e., affirmation/disaffirmation), there may be three: unconditional affirmation, unconditional disaffirmation, and conditional. Quantitative analyses of time to answer, eyeball shifting, and pre-beginning behavior suggest that unconditional disaffirmation may not be dispreferred relative to unconditional affirmation. Instead, conditional answers may be dispreferred. Results begin to reconcile anomalies and expand our current understanding of preference organization. Data are in American English.

Cognitive accessibility predicts word order of couples’ names in English and Japanese

Article

Feb 2020

We investigate the order in which speakers produce the proper names of couples they know personally in English and Japanese, two languages with markedly different constituent word orders. Results demonstrate that speakers of both languages tend to produce the name of the person they feel closer to before the name of the other member of the couple ( N = 180). In this way, speakers’ unique personal histories give rise to a remarkably systematic linguistic generalization in both English and Japanese. Insofar as closeness serves as an index of cognitive accessibility , the current work demonstrates that systematicity emerges from a domain-general property of memory.

Resonance in dialogue: The interplay between intersubjective motivations and cognitive facilitation

Abstract

Recommended publications

What's in a dialogue? On the dynamics of meaning-making in English conversation

Challenges of releasing audio material for spoken data: The case of the London-Lund Corpus 2

'What and then a little robot brings it to you?' The reactive what-x construction in spoken dialogue

On the London-Lund Corpus 2: Design, challenges and innovations