4961

Unpacking the Relationship Between
Formulaic Sequences and Speech Fluency
on Elicited Imitation Tasks: Proficiency
Level, Sentence Length, and Fluency
Dimensions
XUN YAN
University of Illinois at Urbana-Champaign
Urbana, Illinois, United States

Previous research has provided ample evidence for the processing
advantage of formulaic sequences, leading researchers and teachers to
argue for its facilitation of speech fluency. However, few studies have
examined how the processing of formulaic sequences interacts with
speaker proficiency and task difficulty; even fewer studies have investigated how formulaic sequences facilitate different dimensions of
speech fluency. To address these gaps, this study examined the impact
of formulaic sequences on speech fluency for both first and second
language speakers (N = 269) across proficiency levels on elicited imitation tasks. Participants’ speech fluency was measured on both rate
and pausing features. Results from linear mixed-effects models reveal
that formulaic sequences had a significant effect on the reduction of
pauses, but not on speech rate. The effect on pausing was stronger in
the processing of long sentences and on intermediate second language speakers. These results suggest that formulaic sequences have
differential impacts on the rate and pausing dimensions of speech fluency, and the impacts are further conditioned by speaker proficiency
and task difficulty. Findings of this study have both theoretical and
pedagogical implications regarding the acquisition of formulaic
sequences and the development of speech fluency.(ancestor::component/descendant::publicationMeta/titleGroup/title=Reviews’))"
doi: 10.1002/tesq.556

A

s a long-recognized linguistic phenomenon, formulaic sequences
have been extensively studied from both cognitive and sociocultural perspectives in the fields of corpus linguistics, psycholinguistics,

second language acquisition, and second language (L2) pedagogy
(Wray, 2002). The findings from corpus linguistics and
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© 2019 TESOL International Association


psycholinguistics research on first language (L1) speakers suggest that
(1) formulaic sequences are ubiquitous in natural language use and
(2) formulaic sequences create a processing advantage that alleviates
the cognitive pressure of speech production and facilitates the flow of
conversation between interlocutors (Christiansen & Chater, 2016; Conklin & Schmitt, 2012). Although a similar processing advantage was
observed in advanced-level L2 speakers (Conklin & Schmitt, 2008;
Jiang & Nekrasova, 2007), scholars remain dubious about whether it
applies equally across speakers of different proficiency levels (Northbrook & Conklin, 2019; Wray, 2017).
In L2 teaching and assessment research, formulaic sequences have
also gained popularity as a target construct in the development of
fluency and overall language proficiency. With focused instruction,
L2 speakers tend to use more formulaic sequences, and their
speech fluency improves over time (Boers, Brussels, Kappel, Stenfers, & Demecheleer, 2006; Serrano, Stengers, & Housen, 2015;
Wood, 2009). However, in those studies, fluency tended to be measured through rate features (e.g., speech rate, mean length of run),
but less often through pausing features (although Wood [2006,
2009] incorporated pausing when computing mean length of run).
Little is known about how the processing advantage of formulaic
sequences manifests through different dimensions of speech fluency.
Motivated by these gaps in the literature, this study examined
whether formulaic sequences present a similar processing advantage
on the rate and pausing dimensions of fluency and whether the
processing advantage applies equally to L2 speakers across proficiency levels.

BACKGROUND AND MOTIVATION
Processing Advantage of Formulaic Sequences: Evidence
From L1 and L2 Speakers
Formulaic language has been referred to using different terms: formulae, formulaic sequences, prefabricated patterns, multiword units or
sequences, to mention a few (see reviews by Arnon & Christiansen,
2017; Wray, 2002). It also covers a broad range of phenomena such as
idioms, collocations, phrasal verbs, binomials, and lexical bundles
(Carrol & Conklin, 2019). This article focuses on what usually are
referred to as lexical bundles, which are sequences of words that occur
frequently in language, are generally corpus derived, and may or may
not constitute a complete utterance. However, these bundles have also

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been referred to as formulaic sequences or units in the literature. For
convenience, I use the umbrella term formulaic sequences to describe
this linguistic phenomenon in the remainder of this article. The
prevalence of formulaic sequences in natural language leads scholars
to believe that formulaic sequences are stored holistically in the
speaker’s mental lexicon and thus are retrieved and processed more
efficiently than noncollocated word sequences (Peters, 1983). The
processing advantage is warranted by three assumptions: (1) limited
cognitive resources for online processing (e.g., attention, working
memory) encourage chunking of linguistic input, (2) the processing
of high-frequency linguistic items is more automatic than that of lowfrequency items, and (3) grammar and the lexicon are not completely separable. L1 speakers can internalize a bank of formulaic
sequences, and their language production is marked by a flexible

alternation between linguistic creativity and chunking (Ellis, 2002;
Nattinger, 1980) or, in Sinclair’s (1987) terms, between the application of the open choice principle (words and rules) and the idiom principle (chunking). That said, it should be noted that despite the
widespread belief in the processing advantage of formulaic
sequences, there has not been concrete evidence to support the
holistic representation of formulaic sequences in the brain; however,
recent event-related potential research found the activation of a mental “template” in the brain when speakers process formulaic
sequences versus nonformulaic sequences (Siyanova-Chanturia, Conklin, Caffarra, Kaan, & van Heuven, 2017, p. 111).
There has been an abundance of psycholinguistic evidence for the
processing advantage of formulaic sequences from L1 speakers. Previous research utilized self-paced reading tasks, elicited imitation tasks,
and eye-tracking techniques to measure formulaic sequence processing
both in isolation and embedded in texts. Findings of these studies
reveal that L1 speakers—both children and adults—process formulaic
sequences faster and more accurately than nonformulaic sequences in
both comprehension and production modes (Bannard & Matthews,
2008; Conklin & Schmitt, 2008; Siyanova-Chanturia, Conklin, & Schmitt, 2011; Siyanova-Chanturia, Conklin, & van Heuven, 2011; Sosa &
MacFarlane, 2002; Tremblay, Derwing, Libben, & Westbury, 2011;
Underwood, Schmitt, & Galpin, 2004).
Studies have also revealed a processing advantage of formulaic
sequences among advanced and intermediate L2 speakers (Conklin &
Schmitt, 2008; Jiang & Nekrasova, 2007; Yeldham, 2018). Findings of
these studies seem to indicate a close relationship between knowledge
of formulaic sequences and proficiency level. That is, an internalized
knowledge of formulaic sequences is more likely to exist among
advanced and intermediate L2 speakers than among low-proficiency
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FORMULAIC SEQUENCES AND SPEECH FLUENCY


speakers (Serrano et al., 2015; Siyanova-Chanturia, Conklin, & Schmitt,

2011; Valsecchi et al., 2014; although see Northbrook & Conklin,
2019, for an exception). However, when accounting for the processing
advantage of formulaic sequences, it might also be the case that proficiency is confounded with exposure or familiarity. Several studies have
shown that when (low-proficiency) L2 speakers are familiar with the
formulaic sequences (e.g., a similar expression existent in their L1
or a lexical bundle appearing in their textbooks), they demonstrate
the typical processing advantage as do L1 speakers (Carrol & Conklin,
2014, 2017; Northbrook & Conklin, 2019). These findings align with
predictions of a usage-based approach to L2 acquisition, in which
exposure influences memory and processing of linguistic forms. In this
approach, proficiency often serves as a proxy for exposure, such that
higher proficiency participants have sufficient exposure to lead to a
processing advantage whereas low proficiency participants have not
had enough exposure to as many formulaic sequences. In either
account, it remains underexplored whether the processing advantage
of formulaic sequences applies equally between intermediate and
advanced L2 speakers.
To complicate the matter further, research also suggests that the
processing advantage for L2 speakers is conditioned by not only the
speaker’s proficiency level but also the difficulty level of language
tasks used to elicit the processing of formulaic sequences (Yeldham,
2018). On one hand, the processing advantage might exist only after
a threshold proficiency level is reached or vary in degree according
to proficiency level. On the other hand, the processing advantage
might be needed or triggered only when the language tasks are sufficiently challenging. Therefore, the processing advantage of formulaic
sequences for L2 speakers remains an open question.

Formulaic Sequences and the Development of L2 Speech
Fluency
Speech fluency is a multifaceted, multdimensional construct. Lennon (1990) defined fluency in both broad and narrow senses. In the

broad sense, fluency is synonymous with overall language proficiency;
in the narrow sense, fluency refers to the temporal features of speech
in two large dimensions, namely, rapidity (e.g., a high speech rate)
and smoothness (e.g., the lack of disfluency). Skehan (2003) further
divides the smoothness dimension into breakdown fluency (pausing)
and repair fluency, although pause and repair are closely associated
cognitive traces of speech disfluency. Findings from empirical research

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have repeatedly confirmed that, although rapidity and smoothness
constitute distinct constructs in L2 learning, teaching, and assessment,
both dimensions have been observed to be strong predictors of speakers’ language proficiency (Ginther, Dimova, & Yang, 2010; Iwashita,
Brown, McNamara, & O’Hagan, 2008).
The abundance of psycholinguistic evidence has led researchers
and practitioners in L2 pedagogy and assessment to associate the
acquisition of formulaic sequences with the development of L2 speech
fluency. Theoretically, this is a reasonable speculation in that nativelike proficiency or fluency is marked by a high proportion of chunking and formulaic language use (Pawley & Syder, 1983). From a pedagogical standpoint, formulaic sequences can be used as a strategy to
help L2 speakers alleviate the processing load and disfluency in
speech production. Following this line of reasoning, focused instruction of formulaic sequences should also facilitate the development of
L2 speech fluency. That said, it is important to note that the psycholinguistic studies reviewed above only examined the processing
advantage as the dependent variable, but not speech fluency (e.g.,
speech rate, pausing).
The association between formulaic sequences and L2 fluency can be
supported by a cognitive perspective. Segalowitz (2010) identified
three domains of L2 speech fluency: cognitive, utterance, and perceived. The relationship among the three domains is that cognitive fluency results in observable utterance fluency of the speaker, which
further leads to the listener’s perception of fluency. Based on Levelt’s

(1989) blueprint for the speaker, Segalowitz speculated that disfluencies can occur at seven different stages of speech production related
to the processing of lexico-grammar: microplanning, grammatical
encoding, lemma retrieval, morpho-phonological encoding, phonetic
encoding, articulation, and self-perception. The ability to retrieve and
produce grammatical and lexical items effortlessly during speech production results in a higher speech rate and the perception of higher
fluency from listeners. Findings from empirical studies are overall in
support of this association (de Jong, 2016; Segalowitz, 2016; Wright &
Tavakoli, 2016); however, pedagogically, a deeper understanding
of the link between the processing advantage of formulaic sequences
and the resultant changes in utterance fluency features can help language teachers and testers better assess and monitor the acquisition of
formulaic sequences by language learners.
Studies have shown a significant effect of focused instruction on the
use of formulaic sequences in speech (Wood, 2009) as well as a positive correlation between the use of formulaic sequences and rate features of speech fluency (Boers et al., 2006; Ejzenberg, 2000; Towell,
Hawkins, & Bazergui, 1996). To some extent, these findings support
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FORMULAIC SEQUENCES AND SPEECH FLUENCY


the commonly held pedagogical assumption that the use of formulaic
sequences facilitates the development of L2 speech fluency. Formulaic
sequences are articulated faster than nonformulaic sequences as words
within a formulaic sequence tend to be phonetically reduced due to
holistic processing (Arnon & Cohen Priva, 2013; Bybee & Scheibman,
1999). In this connection, it can be hypothesized that perception of
higher speech fluency is a result of phonetic reduction on the formulaic sequences, which leads to higher speech rate. However, there
seems to another plausible explaination, that is, the holistic processing
of formulaic sequences alleviates the cognitive processing load and
thus reduces disfluencies in speech. To further test these two hypotheses, the processing of formulaic sequences needs to be embedded in
individual sentences and be examined in terms of its impact on both

the rate and pausing features. Previous research examined the processing of formulaic sequences in its own right, but whether formulaic
sequences lead to faster speech rate at the sentence level remains largely underexplored. Moreover, little is known about the relationship
between formulaic sequences and the pausing dimension of fluency;
investigations of this relationship can help us better understand the
processing advantage of formulaic sequences and its manifestations in
speech fluency.

The Processing of Formulaic Sequences on Elicited Imitation
Tasks
Speech fluency is influenced by not only the proficiency level of
the speaker but also the difficulty of the speaking task (Robinson,
2001; Skehan, 1998). Therefore, in addition to speaker proficiency, it
is reasonable to posit that task difficulty also influences the processing of formulaic sequences; Sinclair (1987) contended that, to facilitate communicative efficiency, L1 speakers prefer formulating
utterances from chunks and will break formulaic sequences down to
the individual word level only when necessary. Although both openended and more controlled speaking tasks have been used to examine speech fluency, the difficulty of controlled speaking tasks is relatively easier to manipulate. This study employed elicited imitation, a
psycholinguistic task used to measure L2 proficiency that asks participants to listen to and repeat a series of sentences (van Moere, 2012;
Yan, Maeda, Lv, & Ginther, 2016). Elicited imitation presents a clear
advantage over open-ended speech tasks for measuring the processing of formulaic sequences. That is, researchers can construct the
stimulus sentence using a preselected set of formulaic sequences.

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Asking the participants to repeat the sentences verbatim forces them
to use the formulaic sequences. If the participants are familiar with
the formulaic sequences, it is likely to be easier for them to repeat
the sentences. Meanwhile, the task also elicits speech production,
allowing for the analysis of speech fluency.

In summary, decades of research on formulaic sequences reveals
converging evidence for its processing advantage and impact on
speech fluency. However, few studies have investigated how formulaic
sequences interact with speaker’s proficiency level and task difficulty
and how they influence different dimensions of speech fluency. Motivated by these gaps, this study investigated (1) whether formulaic
sequences create an equal processing advantage for L1 and L2 speakers across proficiency levels when produced in sentences of varying
lengths and, if so, (2) how the processing of formulaic sequences
influences rate and pausing dimensions of speech fluency. In order
to gauge the facilitation effect of formulaic sequences while controlling other variables affecting sentence processing and production,
this quasi-experimental study utilized elicited imitation tasks to examine the processing of formulaic sequences within individual sentences.

RESEARCH QUESTIONS
This study employed a quasi-experimental design to examine the
processing of formulaic sequences on elicited imitation tasks by
both L1 and L2 speakers. Two research questions (RQs) were formulated to guide this study, with each question consisting of four
subquestions:
RQ1: How does the presence of formulaic sequences influence
speech rate?
1. Does the presence of formulaic sequences have a significant
effect on speech rate?
2. Does sentence length have a significant effect on speech rate?
3. Does proficiency level have a significant effect on speech rate?
4. Is there any significant interaction among the three independent variables?
RQ2: How does the presence of formulaic sequences influence the
number of silent pauses?
1. Does the presence of formulaic sequences have a significant
effect on the number of silent pauses?
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2. Does sentence length have a significant effect on the number of
silent pauses?
3. Does proficiency level have a significant effect on the number
of silent pauses?
4. Is there any significant interaction among the three independent variables?

METHOD
Participants
Participants in this study were 17 L1 speakers of English and 252
English as a second language (ESL) freshmen enrolled in an English
for academic purposes course at a large U.S. university. The L1 speakers of English were all native speakers of North American English,
recruited as a baseline control group. Descriptive statistics of the ESL
students’ TOEFL iBT scores are included in Table 1. Following the
score interpretation guidelines by ETS and the Common European
Framework of Reference (CEFR), the students’ proficiency levels were
labeled as high intermediate (n = 89) to advanced (n = 163), largely
corresponding to the B2–C1 levels (Council of Europe, 2011; Papageorgiou, Tannenbaum, Bridgeman, & Cho, 2015). The ESL students
had larger score differences in their receptive subskills (i.e., listening
and reading) than in productive subskills (i.e., speaking and writing).
This restricted range of proficiency might have an impact on the interpretation and generalizability of the results. However, this group of
students is representative of the ESL population in U.S. universities.
Though not as proficient as their L1 peers, these students are not lowproficiency L2 speakers and can be reasonably expected to have developed knowledge of high-frequency formulaic sequences. The overwhelming majority of the participants were L1 Mandarin Chinese
speakers (n = 236), with only a few participants from other L1 backgrounds: Korean (n = 7), Hindi (n = 3), Portuguese (n = 2), Spanish
(n = 2), Italian (n = 1), and Vietnamese (n = 1). The age of the participants ranged between 18 and 25 years.

Identification of Formulaic Sequences
This study targeted a list of high-frequency formulaic sequences
identified in a corpus-driven approach. Formulaic sequences were

defined in terms of frequency and mutual information (MI) score.
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TABLE 1
Descriptive Statistics of L2 Participants’ TOEFL iBT Scores
Intermediate

Reading
Listening
Speaking
Writing
Total

Advanced

N

M

SD

N

M

SD

89
89
89
89
89

22.55
21.52
20.08
22.06
85.95

2.18
2.43
1.63
2.00
3.08

163
163
163
163
163

25.83
24.76
21.30
23.44
95.19

2.58
2.75
2.28
2.58
4.91

Specifically, a list of commonly used spoken formulaic sequences was
selected from the academic spoken formula lists in Simpson-Vlach and
Ellis (2010) and Schmitt (2004). The formulaic sequences were then
cross-validated with the Corpus of Contemporary American English for
frequency and MI score, and all of them had a frequency higher than
10 occurrences per million words and an MI score larger than 3. The
overwhelming majority of the bundles occurred more than 20 times
per million words, a suggested frequency cutoff for large corpora
(Biber, Conrad, & Cortes, 2004). The mean occurrence of these
sequences was around 50 times per million words across forms. All formulaic sequences were three to four words long. Although it is customary to select four-word lexical bundles in research (Biber et al.,
2004), a number of three-word bundles are complete by themselves
(e.g., all sorts of, as well as). Therefore, in this study, both three- and
four-word bundles were selected. Sequences with figurative meaning
were excluded because the processing of those sequences is not tuned
to frequency the same way literal formulaic sequences are (SiyanovaChanturia & Martinez, 2015). When selecting formulaic sequences, the
frequency criterion was prioritized because word frequency influences
the fluency and disfluency in lexical production of both L1 and L2
speakers (de Jong, 2016). However, a balance was strived for to select
formulaic sequences across three functional types (i.e., referential
expressions, stance expressions, and discourse organizers) and syntactic categories (i.e., verb phrase fragments, dependent clause fragments,
noun and prepositional phrase fragments; Biber et al., 2004; SimpsonVlach & Ellis, 2010). Similarly, a balance was also strived for concerning the position at which formulaic sequences occurred in the sentences (i.e., toward the beginning, middle, or end of the sentence).
The list of target formulaic sequences is presented in the Appendix.
The selected formulaic sequences were piloted on 20 ESL students (10
intermediate and 10 advanced). All of them were able to understand

the meaning of the sequences and reported using them frequently in
speech or conversation.
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Elicited Imitation Task
The formulaic and nonformulaic sequences were embedded in elicited imitation tasks. The design of the tasks followed recommendations from previous literature, including a range of sentence length
levels and the insertion of a delay between the stimulus and repetition,
as well as the use of noncognitively challenging disruption tasks to prevent parroting and force the participants to process the meaning of
the sentences (Vinther, 2002; Yan et al., 2016). Four parallel forms
were developed, each comprising 24 sentences. In each set of 24 sentences, only 12 sentences contained formulaic sequences. These two
conditions were also evenly distributed across three length bands. All
the sentences were authentic such that they either conveyed important
information about college life or were sentences that college students
frequently hear or say on campus. The topics covered in those sentences included health insurance, academic coursework, student clubs
and activities, lifestyle on campus, and lifestyle in the midwestern United States. The elicited imitation tasks were administered in a computer lab. Participants were randomly assigned to one of the four
forms. The tasks were timed: Participants had 20 seconds to repeat
each sentence. During the test session, each participant had the
opportunity to complete two practice items before hearing the 24 target sentences.

Data Analysis
The present quasi-experimental study employed a mixed-effects,
repeated-measures design, with three independent variables and two
dependent variables.
Independent variables. The three independent variables were the
presence of formulaic sequences (formulaicity), proficiency, and task
difficulty. The three independent variables were fully crossed. Formulaicity was a two-level within-subject factor (i.e., with vs. without formulaic sequences). Although L2 participants’ proficiency levels were
regarded to range between L2 intermediate to L2 advanced, proficiency

was treated as a continuous variable in the statistical model, which was
operationalized in terms of the participants’ TOEFL total score1; however, for the consideration of interpretability, descriptive statistics of fluency features were also reported by proficiency levels. Task difficulty of
1

The TOEFL scores were the official scores the students submitted for university enrollment, and all the participants were in their first semester at the time of the study.

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elicited imitation tasks was narrowly operationalized as sentence length.
This within-subject factor consisted of three levels: short (eight to nine
syllables), medium (15 to 16 syllables), and long (20 to 21 syllables) sentence bands. It should be acknowledged that task complexity involves
not only linguistic and cognitive complexity but also task condition
(Robinson, 2001; Skehan, 2003), all having an impact on task difficulty.
For elicited imitation tasks, although a range of task design features can
have an impact on sentence repetition responses, sentence length was
the strongest predictor of task difficulty (Perkins, Brutten, & Angelis,
1986; Yan et al., 2016). That is, as the sentence becomes longer, the level
of cognitive pressure for elicited imitation tasks increases, requiring the
speaker to be more automatic at chunking the sentences. Considering
findings from previous research on elicited imitation and the design
complexity of the experiment, sentence length can be a reasonable
point of departure for examining the impact of task difficulty on the
processing advantage of formulaic sequences.
In order to better investigate the effects of the independent variables,
efforts were made to ensure that all sentences were comparable in terms
of syntactic, lexical, and phonological complexity and that the task conditions were standardized across sentences and participants. For syntactic complexity, the sentences were evenly distributed across four types of
subordination; that is, all sentences had one adjective, noun, or adverbial subordinate clause, or no subordination. In terms of phonological

and lexical complexity, no word in the sentence contained more than
three syllables or two morphemes. In addition, around 90% of the
words in each sentence were from the K1 and K2 word lists (Heatley &
Nation, 1994), with the remaining 10% from the academic word list.
The formulaic sequences used at each length band across the four
forms were also comparable in terms of mean frequency.
Dependent variables. Elicited imitation responses were analyzed
through PRAAT, Version 5.4.05 (Boersma & Weenink, 2015). A script
developed by de Jong and Wempe (2009) was used to automatically
extract values of two fluency variables: speech rate and number of
silent pauses. Speech rate was operationalized as the total number of
syllables divided by the sum of speech time (syllable per second).
Silent pause was defined as a duration of silence for 0.25 seconds or
longer, which was the minimum duration threshold of silent pauses
recommended by de Jong and Bosker (2013). These two variables were
selected because they are the most commonly used fluency measures
in L2 research, representing the rapidity and smoothness dimensions
of speech fluency, respectively. The two measures have also demonstrated strong validity in predicting fluency and overall proficiency
(Ginther et al., 2010). Specifically, speech rate was chosen in lieu of
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FORMULAIC SEQUENCES AND SPEECH FLUENCY


articulation rate because speech rate tends to be a stronger predictor
of fluency and overall proficiency whereas articulation rate is relatively
more stable across speakers (Miller, Grosjean, & Lomanto, 1984).
Number of silent pauses was selected instead of pause duration and filler pauses because it better reflects cognitive fluency and language
proficiency (de Jong & Bosker, 2013). To ensure the reliability of automated fluency measures, 10% of the data were manually analyzed, and
the Pearson correlation between the two methods was .84 for speech

rate and .89 for number of silent pauses. To account for the durational variation of individual elicited imitation responses, silent pause
was normalized to number of silent pauses per second by dividing the
number of silent pauses by the duration of responses.
Statistical analysis. A total of 6,456 elicited imitation responses were
recorded from the 269 participants. Three responses were excluded
from the analysis due to poor recording quality, resulting in a total of
6,453 speech samples. To address the research questions, the descriptive statistics of fluency features were first examined. Then, the lme4
package (Bates, Maechler, & Bolker, 2012) in R (R Core Team, 2012)
was used to run linear mixed-effects models to analyze the impact of
the independent variables on speech rate and number of silent pauses.
In these models, formulaicity, sentence length, and proficiency level
were entered as fixed effects, along with random intercepts for participants and items. Prior to the statistical analyses, screening procedures
were performed to check the normality of the data. No obvious deviations from homoscedasticity or normality were found for both dependent variables. Because participants were randomly assigned to one of
the four forms, the mixed-effects models also included form as a fixed
effect to examine whether speech rate and number of silent pauses of
the participants’ task responses differed substantially across forms. No
significant cross-form difference was observed for either speech rate (F
(3, 226) = 1.05, p = .37) or number of silent pauses (F(3, 226) = 0.85,
p = .47), suggesting that the form effect was negligible.

RESULTS
RQ1: What Are the Main and Interaction Effects of
Formulaic Sequences, Sentence Length, and Proficiency Level
on Speech Rate?
Descriptive statistics for both speech rate and number of silent
pauses across conditions are summarized in Table 2. Tables 3 and 4

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present the summary statistics of the main and interaction effects of
formulaicity, sentence length, and proficiency level on speech rate.
The omnibus tests revealed significant main effects for sentence
length (F(2, 257) = 5.323, p = .005) and proficiency level (F(1, 268) =
25.484, p < .001). The beta coefficients for the contrasts in Table 4
(the fourth column) show that participants’ average speech rate was
0.001 and 0.172 syllables per second faster on the long sentences than
on the medium and short sentences, respectively (bL-S = 0.172, SE =
0.090, t = 1.910, p = .057; bL-M = 0.001, SE = 0.090, t = 0.012, p = .990).
This shows that although speech rate is comparable between long and
medium sentences, it is slower on short sentences. The slower speech
rate on shorter sentences was likely an artifact of timed tasks: shorter
sentences were easier to repeat, and the participants had less pressure
to rush through the repetition within the time limit.
In terms of proficiency level, as expected, proficiency showed a positive relationship with speech rate (bProficiency = 0.314, SE = 0.053, t =
5.911, p < .001), suggesting that higher proficiency speakers repeated
the sentences at a faster speech rate. In contrast, the main effect of
formulaicity did not reach statistical significance (F(1, 1285) = 0.739, p
= .390), suggesting that the presence of formulaic sequences does not

TABLE 2
Descriptive Statistics of Speech Rate and Number of Pauses per Sentence

Speech rate

Number of
pauses

Proficiency
level

Formulaic
sequence

Sentence
length

N

M

SD

M

SD

L1

FS

Short
Medium
Long
Short
Medium
Long
Short

Medium
Long
Short
Medium
Long
Short
Medium
Long
Short
Medium
Long

17
17
17
17
17
17
163
163
163
163
163
163
89
89
89
89
89
89

4.48
4.56
4.85
4.39
4.75
4.61
3.98
4.06
4.07
3.88
4.09
3.99
3.93
3.96
3.90
3.81
3.90
3.91

0.91
0.68
0.58
0.63
0.88
0.65
0.90
0.70
0.69
0.74

0.68
0.69
0.88
0.59
0.65
0.79
0.67
0.72

0.38
0.37
0.57
0.41
0.38
0.71
0.55
1.14
1.47
0.55
1.28
1.72
0.70
1.28
1.85
0.71
1.56
2.29

0.55
0.60

0.70
0.53
0.57
0.75
0.86
1.16
1.38
0.71
1.30
1.45
1.02
1.21
1.52
0.93
1.47
1.75

NoFS
L2 advanced

FS
NoFS

L2
intermediate

FS
NoFS

FS = sentence containing a formulaic sequence; NoFS = sentence containing no formulaic

sequence.
477

FORMULAIC SEQUENCES AND SPEECH FLUENCY


TABLE 3
Significance Tests of Main and Interaction Effects on Speech Rate
Sum Sq

Mean Sq

0.281
4.050
9.694
0.377
0.002
9.600
2.005

0.281
2.025
9.694
0.189
0.002
4.800
1.002

df1

df2

F

p

1
2
1
2
1
2
2

1285
257
268
1285
6157
6137
6157

0.739
5.323
25.484
0.496
0.006
12.618
2.635

.390
.005
<.001
.609
.939
<.001
.072

SE

df

t

p

2.399
0.020

0.099
0.089

527
1504

24.257
0.224

<.001
.823

Medium
Short
–
NoFS 9 Medium
NoFS 9 Short
–

À0.001
À0.172
0.314
À0.125
À0.067
À0.085

0.090
0.090
0.053
0.125
0.126
0.047

523
464
584
1641
1106
6167

–0.012

–1.910
5.911
–0.995
–0.534
–1.818

.990
.057
<.001
.320
.594
.069

Medium 9 Proficiency
level
Short 9 Proficiency level
NoFS 9 Medium 9
Proficiency level
NoFS 9 Short 9
Proficiency level

À0.076

0.047

6154

–1.614

.107

À0.208
0.139

0.047
0.066

6146
6166

–4.447
2.101

<.001
.036

0.123

0.066

6154

1.853

.064

Formulaicity
Sentence length
Proficiency level
Formulaicity 9 Sentence length

Formulaicity 9 Proficiency level
Sentence length 9 Proficiency level
Formulaicity 9 Sentence length 9
Proficiency level

TABLE 4
Coefficient Summary for Main and Interaction Effects on Speech Rate
Fixed effects

Contrast

(Intercept)
Formulaicity
(baseline: FS)
Sentence length
(baseline: Long)
Proficiency level
Formulaicity 9
Sentence length
Formulaicity 9
Proficiency level
Sentence length 9
Proficiency level

–
NoFS

Formulaicity 9
Sentence length 9
Proficiency level

b

have a meaningful impact on the speech rate of participants’
responses on elicited imitation tasks.
There was a significant interaction effect between sentence length
and proficiency level (F(2, 6137) = 12.618, p < .001). That is, for all
speakers, the speech rate on long and medium sentences was faster
than on short sentences; however, the difference becomes larger as
proficiency level of the speakers increases (bS_L9Proficiency = À0.208,
SE = 0.047, t = À4.447, p < .001; bM_L9Proficiency = À0.076, SE = 0.047,
t = À1.614, p = .107). In contrast, the interaction between formulaicity
and proficiency level was not significant (F(1,6157) = 0.006, p = .939),
suggesting that the impact of formulaic sequences is similar for speakers across proficiency levels. The interaction between sentence length
and formulaicity was not significant (F(2, 1285) = 0.496, p = .609). Similarly, there was not a significant three-way interaction between the
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FIGURE 1. Main and interaction effects of formulaicity, sentence length, and proficiency
level on speech rate.

three independent variables on speech rate (F(2, 6157) = 2.635, p =
.072). Taken together, the main and interaction effects of formulaicity
suggest that the presence of formulaic sequences might not have a
substantial effect on the rate dimension of speech fluency. These
results are also reflected in Figure 1, which plots the speech rate
across all six sentence conditions and proficiency levels. Sentences
containing formulaic sequences (FS, represented by black bars) do not

show a consistent advantage over sentences that do not (NoFS, represented by grey bars) across all conditions.

RQ2: What Are the Main and Interaction Effects of
Formulaic Sequences, Sentence Length, and Proficiency Level
on Number of Silent Pauses?
Tables 5 and 6 present the summary statistics of the main and interaction effects of formulaicity, sentence length, and proficiency level on
the number of silent pauses. Overall, there was a significant effect of
sentence length (F(2, 508) = 21.533, p < .001), suggesting that an
increase in processing load (i.e., sentence length) leads to a higher
task difficulty level, which results in an increase in the number of
silent pauses during speech production. According to the beta coefficients in Table 6, on average the long sentences resulted in 0.146 and
479

FORMULAIC SEQUENCES AND SPEECH FLUENCY


TABLE 5
Significance Tests of Main and Interaction Effects on Number of Silent Pauses

Formulaicity
Sentence length
Proficiency level
Formulaicity 9 Sentence length
Formulaicity 9 Proficiency level
Sentence length 9 Proficiency level
Formulaicity 9 Sentence length 9
Proficiency level

Sum Sq

Mean Sq

0.800
2.909
1.694
0.075
0.353
0.973
0.052

0.800
1.455
1.694
0.037
0.353
0.486
0.026

df1

df2

F

p

1
2
1
2

1
2
2

1648.2
508.1
269.0
1648.1
6167.7
6148.7
6167.4

11.847
21.533
25.082
0.554
5.225
7.200
0.388

<.001
<.001
<.001
.575
.022
<.001
.678

TABLE 6
Coefficient Summary for Main and Interaction Effects on Number of Silent Pauses

Fixed effects

Contrast

b

SE

df

t

p

(Intercept)
Formulaicity (baseline: FS)
Sentence length (baseline:
Long)
Proficiency level
Formulaicity 9 Sentence
length
Formulaicity 9 Proficiency
level
Sentence length 9
Proficiency level

–
NoFS
Medium
Short

–
NoFS 9 Medium
NoFS 9 Short
–

0.390
0.105
À0.030
À0.146
À0.068
À0.047
À0.048
À0.025

0.032
0.037
0.037
0.037
0.017
0.052
0.052
0.020

824
1812
897
805
1200
1958
1465

6175

12.050
2.846
À0.793
À3.920
À3.926
À0.901
À0.922
À1.241

<.001
.004
.428
<.001
<.001
.367
.357
.215

0.008

0.020

6164

0.424

.672

0.058

0.020

6157

2.954

.003

0.010

0.028

6175

0.355

.723

À0.015

0.028

6164

À0.520

.603

Formulaicity 9 Sentence
length 9 Proficiency level

Medium 9
Proficiency level
Short 9 Proficiency
level
NoFS 9 Medium 9
Proficiency level
NoFS 9 Short 9
Proficiency level

FS = sentence containing a formulaic sequence; NoFS = sentence containing no formulaic
sequence.

0.030 pauses per second more than did the medium and short sentences, respectively (bL-M = 0.030, SE = 0.037, t = 0.793, p = .428; bL-S =
0.146, SE = 0.037, t = 3.920, p < .001). This substantial increase of
pausing with sentence length indicates that speakers spend more effort
processing longer sentences; they hesitate and pause more frequently
because long sentences contain more information than do shorter sentences.
Similar to speech rate, proficiency level had a significant main effect
on the number of pauses (F(1, 269) = 25.082, p < .001). Proficiency
level showed a negative relationship with silent pauses, suggesting that
speakers of higher proficiency produce fewer pauses when repeating
sentences (bProficiency = À0.068, SE = 0.017, t = 3.926, p < .001).
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However, in contrast to speech rate, the presence of formulaic
sequences also had a significant impact on the number of silent pauses
(F(1, 1648) = 11.847, p < .001). On average, when the participants
repeated a sentence with a three- or four-word formulaic sequence,
they produced about 0.105 pauses per second fewer than repeating a
nonformulaic sentence (bNoFS-FS = 0.105, SE = 0.037, t = 2.846, p =
.004). This result suggests that the presence of formulaic sequences
facilitates speech fluency by reducing the number of silent pauses.
The interaction effect between formulaicity and proficiency level
was significant (F(1, 6167) = 5.225, p = .022). Specifically, the effect of
formulaic sequences decreases as proficiency level increases. There was
not a significant three-way interaction between the three independent
variables on the number of pauses (F(2, 6167) = 0.388, p = .678). The
main and interaction effects for pausing are visually represented in
Figure 2, which plots number of silent pauses across all sentence
length bands and proficiency levels, with the black bars representing
sentences with formulaic sequences and grey bars for sentences without formulaic sequences. There was a gradual increase in the gap
between the black and grey bars as sentence length increases, suggesting that the facilitation effect of formulaic sequences on speech fluency strengthens as the processing load becomes larger (i.e., longer
sentences). Additionally, the differences between black and grey bars
are minimal for the L1 speakers (on the far right of the graph); in
contrast, the differences are the largest for the intermediate L2

FIGURE 2. Main and interaction effects of formulaicity, sentence length, and proficiency
level on silent pauses.
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FORMULAIC SEQUENCES AND SPEECH FLUENCY


speakers, reflecting the interaction effect between formulaicity and

proficiency level.
In sum, the presence of formulaic sequences had a meaningful
impact on the pausing dimension of speech fluency. This result forms
a contrast with the impact of formulaic sequences on the rate feature
of fluency. Moreover, formulaicity had significant interactions with sentence length and proficiency level on pausing, suggesting that the construct of formulaic sequences is related to the cognitive load of
sentence processing (task difficulty) and the speaker’s language proficiency level.

DISCUSSION AND IMPLICATIONS
Findings of this study converge with previous research in that formulaic sequences created a processing advantage and facilitated
speech fluency on elicited imitation tasks for both L1 and L2 speakers.
However, the processing advantage had a differential impact on the
speech rate and number of silent pauses. On one hand, formulaic
sequences did not significantly increase the speech rate of sentence
repetition. On the other hand, formulaic sequences significantly
reduced the number of silent pauses in sentence repetition. This facilitation effect strengthened as the sentences became longer but
appeared more salient on intermediate L2 speakers. Taken together,
the findings suggest that, whereas formulaic sequences have a negligible effect on speech rate, they create a meaningful impact on pausing,
alleviating the cognitive pressure in processing long sentences on elicited imitation tasks. Moreover, this facilitation effect is conditioned
by the proficiency level of the speaker and the difficulty level of the
elicited imitation task. In what follows, I further explicate this differential processing advantage and discuss the pedagogical implications of
this study with respect to the teaching of formulaic sequences and the
development of L2 speech fluency.

Processing Advantages of Formulaic Sequences: Differential
Impacts on Rate and Pausing Dimensions
The presence of formulaic sequences did not have a significant
main effect on speech rate of sentence repetition. This appears at
odds with findings in previous studies that found a processing advantage on rate features as well (Boers et al., 2006; Serrano et al., 2015;
Wood, 2009). There are several possible explanations for the lack of

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effect on speech rate. First, although some utterance features can be
used as proxies of cognitive fluency, others might not be good indications of cognitive fluency. It is possible that speech rate lacks the sensitivity in capturing the nuances in cognitive fluency. Second, even if
speech rate is reflective of cognitive fluency, the absence of an effect
might be because although formulaic sequences are articulated faster,
when placed within a sentence the boost in speech rate might be
washed away by the rest of the sentence (i.e., nonformulaic
sequences). In this study, even in the case of short sentences, the formulaic sequence constituted less than half of the sentence. It is possible that if the sentences consisted of only formulaic language, the
impact on speech rate would be observed.
In contrast, the processing advantage of formulaic sequences manifests more strongly on the pausing dimension. The presence of formulaic sequences helps reduce the processing load and lessen the pauses
during sentence repetition. However, the facilitation from formulaic
sequences is not necessary unless the processing load or the task difficulty level is high. This effect is partially in line with Sinclair’s (1987)
idiom and open choice principles, where the speaker has the flexibility
to alternate between processing formulaic sequences as holistic lexical
items and processing them word by word; however, the (decision of)
alternation between the two processing strategies depends on the difficulty and cognitive pressure involved in the speech tasks. Taken
together, the differential processing advantages of formulaic sequences
entail that, although the articulation of formulaic sequences may be
phonetically reduced, formulaic sequences are more useful to reduce
the cognitive pressure of sentence processing. Thus, with respect to
the two hypotheses on the processing advantage of formulaic
sequences and speech fluency, the findings of this study suggest that
the impact of formulaic sequences on speech fluency at the sentence
level manifests more on the pausing dimension than on the rate
dimension.

Formulaic Sequences and Speech Fluency: Interaction With
Speaker Proficiency and Task Difficulty
Although formulaic sequences had a significant main effect on
pausing, a significant interaction effect was also observed between formulaicity and proficiency level. The effect of formulaic sequences on
reducing silent pauses showed up more strongly for the intermediate
L2 speakers; in contrast, the processing advantage on pausing was
rather weak for L1 speakers, with only some discernible advantage on

483

FORMULAIC SEQUENCES AND SPEECH FLUENCY


long sentences. This finding suggests that the processing advantage of
formulaic sequences in reducing silent pauses is necessary or more
useful when the proficiency level of L2 speakers is not sufficiently
high. Similarly, focused instruction and learning of formulaic
sequences might be more beneficial for intermediate L2 speakers.
The interaction effect between formulaicity and proficiency level
may seem at odds with previous research, because one would expect L1
speakers to show stronger advantage on the processing of formulaic
sequences. However, it is possible that the contrast occurs because the
repetition tasks in this study, especially those of short- and mediumlength bands, were too easy for the L1 speakers; they do not need (to
benefit from) the facilitation effect of formulaic sequences in order to
repeat the sentences. Support for this interpretation can be found in
previous literature. When examining decontextualized word sequences,
Ellis, Simpson-Vlach, and Maynard (2008) found that, whereas the frequency of word sequences did not make a difference in the speech rate
for L1 speakers, L2 speakers were more sensitive to sequence frequency. Similarly, Serrano et al. (2015) examined the effect of intensive, focused instruction of formulaic sequences on the number and
range of formulaic sequences learners produce in speech; they found
that the instruction benefits intermediate L2 learners the most.

Facilitation Effect of Formulaic Sequences on Speech
Fluency: Extrapolation and Expectation
Admittedly, one might reasonably question whether we can generalize the facilitation effect of formulaic sequences on speech fluency
from elicited imitation tasks to less controlled, communicative speaking tasks. On elicited imitation tasks, the participants are encouraged
to process the meaning of the whole sentence before repeating. The
production of spontaneous speech, though not repetitious, undergoes
multiple stages, loops, and iterations (Levelt, 1989; van Moere, 2012).
These iterative processes force speakers to project ahead in the formulation of utterances, which resembles the response process on elicited
imitation tasks. Therefore, the facilitation effect of formulaic
sequences on speech fluency can be expected to occur in less controlled speaking tasks as well. Similarly, Dechert (1983) argued that
formulaic sequences may anchor the processes necessary for planning
and executing speech in real time, thus serving as a buffer for online
language processing. Based on the findings of this study, it can be further argued that this buffer effect is conditioned by both speaker proficiency and task difficulty. If the speaker’s proficiency level is too low,

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the processing advantage of formulaic sequences might not exist; likewise, if the speaker’s proficiency level well surpasses the difficulty level
of the tasks, even if the speaker has an internalized knowledge of formulaic sequences, they need not process them differently than nonformulaic sequences.
However, it is important to maintain a reasonable expectation for
the facilitation effect of formulaic sequences on speech fluency. In this
study, although formulaic sequences had a significant main effect on
pausing, the effect was smaller than that of sentence length and proficiency level. The mean difference in the number of pauses between
sentences with and without formulaic sequences was only around half
a pause per sentence. This difference is small but reasonable; we
would only expect formulaic sequences to be a facilitator, rather than
a determinant, of sentence processing or speech fluency. That said,

the facilitation effect of formulaic sequences on speech fluency can be
cumulative. In the present study, participants were required to process
only one formulaic sequence in each sentence. The facilitation effect
of formulaic sequences can be expected to increase in free speech production, because the speech tends to be longer and more complex,
and more formulaic sequences can be used in one sentence.

Limitations and Future Research
This study is not without limitations. First, the value of elicited imitation has been subject to a longstanding debate in applied linguistics.
Despite its demonstrated effectiveness in measuring language processing and proficiency, concerns still remain as to its authenticity. Thus,
future research can consider comparing the processing of formulaic
sequences in both controlled (e.g., elicited imitation, read-aloud tasks)
and open-ended tasks (e.g., description tasks). Furthermore, the
length, frequency, and MI score of formulaic sequences, along with
their positioning in the sentences, were controlled to be comparable
across forms and conditions in this study, without causing a considerable deviation from authentic content in each sentence. However,
despite such efforts, there was remaining variability in the frequency
and MI score of formulaic sequences. Future research can consider
converting them into independent variables and examining their
impact on the processing advantages of formulaic sequences and utterance fluency. Similarly, it is also worth examining the impact of different types of lexical bundles, for example, syntactic structure and
functional types (Biber et al., 2004; Simpson-Vlach & Ellis, 2010) as
well as their completeness on speech fluency. In terms of the operationalization of speech fluency, this study focuses on only two
485

FORMULAIC SEQUENCES AND SPEECH FLUENCY


utterance fluency variables. Future research should consider examining other fluency and disfluency features. For example, in the pausing
features, it has been observed in recent literature that pause location
can provide additional insights into language processing in speech
(e.g., Kahng, 2014, 2018). In addition, future research can also consider measuring speech latency (i.e., the amount of time participants

take before starting an utterance) or conduct a qualitative analysis of
repair phenomena in elicited imitation responses to investigate a different dimension of utterance fluency. Investigations of the impact of
formulaic sequences on these variables will enrich our understanding
of the relationship between formulaic sequences and speech fluency.

CONCLUSIONS
The present study unpacks the processing advantage of formulaic
sequences by indirectly investigating the impact of formulaic
sequences on L2 speech fluency on elicited imitation tasks in relation
to speakers’ proficiency level, task difficulty, and dimensionality of
speech fluency. Findings of this study converge with previous research
by providing supportive evidence for the psycholinguistic validity of
formulaic sequences for L2 speakers. However, this study also found
that the processing advantage of formulaic sequences differs on rate
and pausing dimensions of speech fluency. Whereas formulaic
sequences have a negligible effect on speech rate, the use of formulaic
sequences significantly reduces pausing at the sentence level. Moreover, the processing advantage of formulaic sequences is conditioned
by speakers’ proficiency level and task difficulty level. These findings
contribute to research on formulaic language learning and use in the
fields of second language acquisition and psycholinguistics by expanding our understanding of the processing of formulaic sequences and
its manifestations in speech production.
The differential processing advantages of formulaic language also
have important implications for language teaching, learning, and
assessment. They provide some grounds for teaching formulaic
sequences to L2 speakers, especially intermediate L2 speakers who are
still developing automaticity in speech production. However, language
teachers should be reminded that the use of formulaic sequences has
a stronger impact on the smoothness rather than rapidity of speech.
Additionally, teachers and learners should maintain a reasonable
expectation for the impact of formulaic sequences on speech fluency,

because the facilitation of formulaic sequences is by no means large
enough to replace the importance of other linguistic and extralinguistic factors that influence the process of speech production.
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THE AUTHOR
Xun Yan is an assistant professor of linguistics at the University of Illinois at
Urbana-Champaign. His research interests include speaking and writing assessment, psycholinguistic approaches to language testing, and language assessment
literacy. His work can be found in Language Testing, Assessing Writing, System, and
Journal of Second Language Writing.

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