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Phonetic drift reveals interconnected phonological representations in simultaneous
bilinguals: a case study of English and Czech stop consonants
Václav Jonáš Podlipskýa, Šárka Šimáčkováa, Kateřina Chládkováb,c
a Department of English and American Studies, Palacký University Olomouc, Czechia
b Institute of Psychology, Czech Academy of Sciences, Prague, Czechia
c Institute of Phonetics, Charles University, Prague, Czechia
This is a preprint version of the article, accepted for publication as a Research Note in the
International Journal of Bilingualism
Correspondence: Václav Jonáš Podlipský, Faculty of Arts, Palacký University Olomouc,
Křížkovského 10, 77180, Olomouc, Czechia. vaclav.j.podlipsky@upol.cz, +420585633134
Abstract
Purpose: The interconnectedness of phonological categories between the two languages of
early bilinguals has previously been explored using single-probe speech production and
perception data. Our goal was to tap into bilingual phonological representations in another
way, namely via monitoring instances of phonetic drift due to changes in language exposure.
Design: We report a case study of two teenage English-Czech simultaneous bilinguals who
live in Canada and spend summers in Czechia. Voice onset time (VOT) of word-initial voiced
and voiceless stops was measured upon the bilinguals’ arrival to and before their departure
from a two-month stay in Czechia.
Data and Analysis: Each bilingual read the same set of 71 Czech and 58 English stop-initial
target words (and additional fillers) at each time of measurement. The measured VOT values
were submitted to linear mixed effects models, assessing the effects of target language,
measurement time, and underlying voicing.
Findings/Conclusions: After the immersion in a Czech-speaking environment, for both
speakers the count of voiced stops realized as prevoiced (i.e. having negative VOT) increased
and the measured VOT of voiced stops (appearing different for English and Czech initially)
drifted towards more negative (more Czech-like) values in both languages, while no change
was detected for the voiceless stops of either English (aspirated) or Czech (unaspirated). The
results suggest that the bilinguals maintain three-way VOT distinctions, differentiating
voiceless aspirated (English), voiceless unaspirated (Czech), and voiced (English~Czech)
stops, with connected bilingual representations of the voiced categories.
Originality: Data on phonetic drift in simultaneous bilinguals proficient in their two
languages has not previously been published.
Significance/Implications: We show that observing phonetic shifts due to changes in the
ambient linguistic environment can be revealing about the organization of phonological space
in simultaneous bilinguals.
Keywords: speech production, phonological representation, phonetic drift, English-Czech
simultaneous bilinguals, voice onset time
1. Introduction
The linguistic competence of a bilingual speaker is not the sum of two separate monolingual
competences (Grosjean, 1989). Instead, it forms a unified system (Cook, 1992). This is seen
in cross-language interactions observed both on the level of linguistic representations (e.g.
Barlow, Branson, & Nip, 2013; Flege & Eefting, 1987; Sebastián-Gallés, Echeverría, &
Bosch, 2005), and on the level of online speech processing (e.g. Goldrick, Runnqvist, &
Costa, 2014; Jacobs, Fricke, & Kroll, 2016; Olson, 2013). Research has documented cross-
language influences indicating that a bilingual’s two languages are not isolated from each
other even for early sequential and/or simultaneous bilinguals. Even though such bilinguals
often display a differentiation between speech sounds of one language and similar sounds of
their other language (Barlow et al., 2013; Simonet, 2010; Yusa, Nasukawa, Koizumi, Kim,
Kimura, & Emura, 2010), they still differ in phonetic realization from monolingual speakers
of each language (e.g. Flege, 1987; Fowler, Sramko, Ostry, Rowland, & Hallé, 2008; Hazan
& Boulakia, 1993).
Reports of a null difference between bilingual and monolingual performance are less
common. For example, Antoniou, Best, Tyler, & Kroos (2010) found that early Greek–
Australian-English bilinguals could produce voice onset times (VOT) of stop consonants, an
acoustic correlate of voicing, indistinguishable from the Greek monolinguals or from the
Australian-English monolinguals if the language context during data elicitation was kept
strictly monolingual. However, even when a study finds no difference between bilingual and
monolingual performance, that does not guarantee that these bilinguals have independent
underlying phonological representations for each language. Sundara & Polka (2008) argue
that evidence of a bilingual differentiating similar sounds in production must be matched by
evidence from perception. They compared perceptual discrimination of the (French) dental
and (English) alveolar voiced stops by Canadian French-English simultaneous bilinguals and
early sequential bilinguals, monolingual speakers of each language, and native speakers of
Hindi (where dental and retroflex stops contrast). They found the early sequential bilinguals’
performance to be based on a merged category. The simultaneous bilinguals appeared to have
a separate stop category for each language, even in perception. Interestingly, their
performance was similar to that of the Hindi speakers but differed from that of the English
monolinguals.
Another way of tapping into phonological representations is via monitoring phonetic
drift, i.e. shifts that occur in response to a change of the ambient linguistic environment (see
Chang, 2019, for a review of the phenomenon). Phonetic adjustments induced by recent input
have been documented for monolinguals (as shown by studies of perceptual adaptation
[Cutler, 2012] and phonetic convergence [Pardo, 2013]), for late non-balanced bilinguals in
L2 (Tobin, Nam, & Fowler, 2017) or both in L2 and L1 (Sancier & Fowler, 1997), and in L1
even for inexperienced L2 learners exposed to the L2 for a relatively short time (Chang, 2012,
2013). Data revealing phonetic drift in simultaneous or early sequential bilinguals proficient
in their two languages is not available to date. The few longitudinal case studies monitoring
L2 and L1 development in early L2 learners which attest phonetic shifts due to exposure are
studies only of the early stages of L2 acquisition (the first 7 months for Simon’s [2010]
learner and the first 20 months for the learner in Yang, Fox, & Jacewicz [2015]). The current
study measures phonetic drift in teenage simultaneous bilinguals to investigate their
representations of similar sounds. We examine the VOT of stop consonants in English and
Czech, languages with different phonetic implementation of the voiced and voiceless
phonemes (short vs long positive VOT in English, and negative vs short positive VOT in
Czech1). Although studies with children simultaneously acquiring two languages with a
difference in the phonetic implementation of stop voicing similar to that between English and
Czech report separate phonetic categories for phonologically voiceless but not for voiced
stops (e.g. Johnson & Wilson, 2002), by adulthood, bilinguals seem to produce language-
specific monolingual-like voiced stops in their two languages (Sundara, Polka, & Baum,
2006). However, as suggested above, having non-identical realizations for equivalent L1 and
L2 sounds does not mean that these sounds are equally well separated at a higher level of
representation. An L1-L2 link at a phonemic level of representation of /b, d, ɡ/ (and possibly
/p, t, k/) may be revealed by an L1-L2 concurrent phonetic drifting in response to a recent
change in the input, such as travelling to another country for summer holidays. A change in
the linguistic environment inducing a shift in the phonetic implementation of stop voicing in
both languages (in the direction of the current input language) can be interpreted as evidence
for a connected phonological representation of such sounds.
We measured the VOT of word-initial stops of two teenage Canadian English-Czech
simultaneous bilinguals (sisters) upon their arrival to and then before their departure from a
two-month stay in Czechia. Our research questions were: (1) What VOTs do our simultaneous
(non-balanced) bilinguals produce for phonologically voiced and voiceless stops in each
language? (2) Do any of their VOT values change in response to the change of the ambient
linguistic environment? (3) If so, does the change occur only in the language of the current
environment or in both languages, reflecting a connection of phonological representations
between the bilinguals’ languages?
2. Method
2.1 Participants
The speakers volunteered to participate. They were two female simultaneous English-Czech
bilinguals dominant in English, two sisters labeled herewith as A and B, A aged 13 and B
aged 16 at the time of the recording. They were born and live in Toronto, Canada, with their
Canadian father and their Czech mother. Before entering elementary education at the age of 6,
each sister had had extensive exposure to Czech from their mother at home, their mother’s
parents during regular 3- to 4-month visits to Czechia every summer, as well as during the
grand-parents’ three-week visits to Canada every winter. After the age of 6, they continued
speaking Czech primarily with their mother, and also their grand-parents whom they saw in
Canada every winter (about 3 weeks) and in Czechia every summer (2 months).
2.2 Stimuli
The material consisted of a list of 71 monosyllabic or disyllabic (stress-initial) Czech and 58
monosyllabic English stop-initial words, and 46 Czech and 15 English filler words. The initial
stops had different places of articulation (see Table 1 for the exact counts) and were followed
by vowels of differing heights (see Table 2).
Table 1: Numbers of stop-initial stimulus words split by places of articulation.
Czech
English
Labial
37
28
Coronal
24
22
Dorsal
10
8
Total
71
58
Table 2: Numbers of stop-initial stimulus words split by the height of the first vowel.
Czech
English
High
25
24
Mid
23
10
Low
23
24
Total
71
58
2.3 Procedure
Upon arrival to Czechia, the speakers were told the purpose of the recordings was to monitor
changes of their pronunciation over the course of their stay in the Czech-speaking
environment. No other details were provided. First, the participants were implicitly
familiarized with the stimulus words, hearing them in conversation with the data collector
(their Czech cousin) one day prior to the first recording session, which took place two days
after their arrival to Czechia.
In the first session itself, the speakers were presented with each of the stimulus words
once, on the screen of a computer, one by one in random order but in two blocks split by
language, at a fixed interval of 2 s for the English and 5 s for the Czech words, and they read
them out loud, in isolation without any carrier phrase. An immediate repetition was elicited by
the data collector in case of unclear pronunciations or mistakes. A Zoom H4n portable
recorder was used for recording the speech at 16-bit and 44.1 kHz without compression.
The different fixed trial duration for English versus Czech was motivated by allowing
greater time for lexical access in the speakers’ non-dominant language, Czech. Because of this
difference, comparisons of measured VOT for Czech versus English have to be made with
caution, as the longer trial duration could potentially encourage slower speech tempo and thus
lengthen VOT in Czech relative to English. However, the main comparison is between
recording sessions within each language and importantly, the same procedure and stimulus
words were used again in the second recording session at the end of the speakers’ two-month
stay in Czechia (59 days after session 1). The comparability of the two recording sessions
within each language allowed for a reliable assessment of the effect of the immersion stay on
VOT production in each language.
2.4 Measurements and analysis
After excluding noisy or erroneous recordings (8 in total), but including occasional repeated
productions of a word, 267 and 268 initial stops could be analyzed for speakers A and B
respectively. Praat (Boersma &Weenink, 2019) was used to manually label their VOT, i.e.
time from the stop release to the first zero crossing of periodicity detectable in the waveform
and broadband spectrogram that either followed (positive VOT) or preceded (negative VOT)
the release. The labelling was performed by the data collector and corrected by the first author
manually.
Per speaker, the measured VOT values were submitted to a linear mixed effects model,
lme4 and lmerTest packages (Bates, Mächler, Bolker, & Walker, 2015; Kuznetsova,
Brockhoff, & Christensen, 2017), in R (R Core Team, 2019) with Language, Underlying
voicing, and Session as fixed factors with orthogonal sum-to-zero contrasts (Czech -0.5 vs
English +0.5, voiced -0.5 vs voiceless +0.5; 1st session -0.5 vs 2nd session +0.5), and Word
as a random factor. Comparison of estimated means across factor levels was carried out with
the emmeans package (Lenth, Singmann, Love, Buerkner, & Herve, 2018).
3. Results
Analyzing first the number of occurrences of phonologically voiced stops realized as
prevoiced (i.e. having negative VOT), we found that for both speakers and both languages the
incidence of prevoiced stops increased between sessions: for speaker B for Czech, the number
of prevoicings increased from 9 out of 28 stops measured in session 1 to 15 out of 28 stops in
session 2 (χ2(1) = 2.63, p = .1052), and for English from 4 out of 32 to 13 out of 33 (χ2(1) =
6.08, p = .0136). Similarly for speaker A for Czech, the number of prevoicings rose from 12
out of 29 stops in session 1 to 18 out of 28 (χ2(1) = 3.00, p = .0834), and for English from 8
out of 31 to 25 out of 32 (χ2(1) = 17.28, p < .0001).
Figure 1. Violin plots of the measured VOT values (in s) of word-initial voiceless and voiced
stops per speaker, language, and session. The colored shapes represent density plots and are
trimmed at the edges to the range of the data. Filled symbols show means.
The measured VOT values for each speaker are shown in Figure 1. For both speakers,
the linear mixed effects models detected the following significant effects: Intercept,
Language, Underlying voicing, Session, Language * Underlying voicing, Underlying voicing
* Session; Table 3 gives their estimated effect sizes, t-values and p-values. Unsurprisingly,
the main effects of Language and Underlying voicing show that stops have longer VOT in
English than in Czech, and that voiceless stops have longer VOT than voiced ones. The main
effect of Session showed that overall VOT was shorter in session 2 than in session 1.
As for the predictors addressing our research questions, the interaction effects of
Language and Underlying voicing and the comparison of estimated means listed in Table 4
show that, for both speakers, voiceless stops were produced with different VOT in Czech
versus in English, while for voiced stops any between-language difference was smaller or
non-existent. The interaction of Underlying voicing and Session, with the estimated means
again in Table 4, demonstrates that VOTs differed between session 1 and 2 for voiced stops
for both speakers but to a smaller extent, or not at all, for voiceless ones.
Table 3: Modelled effects on VOT for each speaker. Estimated values are in seconds.
Speaker
Effect
Estimate
t
p
A
Intercept
0.006
2.002
0.048
Language
0.030
5.180
<.001
Underlying voicing
0.089
15.616
<.001
Session
-0.025
-5.656
<.001
Language * Und. voicing
0.050
4.453
<.001
Und. voicing * Session
0.051
5.666
<.001
Language * Session
-0.007
-0.803
0.423
Language * Und. voicing * Session
0.031
1.729
0.086
B
Intercept
0.014
6.617
<.001
Language
0.033
7.696
<.001
Underlying voicing
0.061
14.155
<.001
Session
-0.017
-4.612
<.001
Language * Und. voicing
0.034
3.995
<.001
Und. voicing * Session
0.031
4.193
<.001
Language * Session
-0.002
-0.273
0.785
Language * Und. voicing * Session
0.006
0.413
0.680
Table 4. Estimated means and t-statistics for the two-way interactions.
Speaker
Underlying
voicing
Language /
Session
Mean
95% conf. int.
t-ratio
p
A
voiceless
Czech
0.023
0.013 … 0.033
English
0.077
0.066 … 0.089
-7.103
<.0001
voiced
Czech
-0.041
-0.053 …-0.029
English
-0.036
-0.048 …-0.025
-0.526
0.6000
B
voiceless
Czech
0.020
0.012 … 0.027
English
0.070
0.061 … 0.078
-8.596
<.0001
voiced
Czech
-0.024
-0.033 …-0.015
English
-0.008
-0.017 …-0.0003
-2.524
0.0128
A
voiceless
Session 1
0.050
0.041 … 0.060
Session 2
0.050
0.040 … 0.060
-0.031
0.9754
voiced
Session 1
-0.013
-0.024 … 0.002
Session 2
-0.064
-0.075 …-0.054
7.679
<.0001
B
voiceless
Session 1
0.045
0.038 … 0.053
Session 2
0.044
0.036 … 0.051
0.310
0.7567
voiced
Session 1
-0.00006
-0.008 … 0.008
Session 2
-0.032
-0.041 …-0.024
5.972
<.0001
Although the three-way interaction of Language, Session and Underlying Voicing was
not significant for either speaker, comparison of estimated means shows that in session 1, the
difference in VOT between Czech and English voiced stops was significant for speaker B, and
was of a comparable magnitude for speaker A, though not reaching significance (mean Czech
minus English difference for speaker B = -18 ms, t = -2.210, p = 0.028; for speaker A = -16 ms,
t = -1.482, p =.140), while in session 2 the effect was numerically smaller and no longer
significant for speaker B and was even in the opposite direction for speaker A (mean Czech
minus English difference for speaker B = -13 ms, t = -1.613, p = 0.108; speaker A = +7 ms, t =
0.664, p = 0.507). Besides suggesting a somewhat clearer differentiation of the Czech and
English voiced stops for speaker B than for speaker A, at least at session 1, these comparisons,
as well as visual inspection of the density plots in Figure 1, also show that while it is possible
that before the immersion period (session 1) the Czech vs English voiced stops had different
VOTs, after the immersion (session 2) a difference between Czech and English voiced stops in
VOT was less likely to exist.
Further, a comparison of means shows that for the voiced stops the difference between
sessions 1 and 2 was larger for English than for Czech: for speaker A, 63 ms for English (t =
6.773, p < .0001) vs. 40 ms for Czech (t = 4.138, p < .0001) and for speaker B, 35 ms for
English (t = 4.736, p < .0001) vs. 30 ms for Czech (t = 3.754, p = .0002), also cf Figure 1. No
such language-specific between-session differences were detected for the underlyingly
voiceless plosives in either speaker (all |t| scores < 0.51, all p values > .61).
Finally, Figure 1 suggests somewhat greater cross-linguistic similarity of VOT values
for voiced stops for speaker A than for speaker B, especially for session 2. The significant
two-way interaction of Underlying voicing and Language suggests that there are language-
specific effects on VOT of voiced versus voiceless stops. To inspect those, we carried out
pairwise comparisons of the estimated means for each Underlying voicing and Language. The
comparisons show that speaker B reliably distinguished the Czech vs English voiced stops
(difference = 16 ms, t = -2.524, p = 0.0128), while speaker A did so to a smaller extent, if at
all (difference = 5 ms, t = -0.526, p = 0.600).
4. Discussion
Several observations on the results of this study can be made. First, our two speakers
produced language-specific VOT values of word-initial stop consonants, as did simultaneous
bilinguals in previous studies (Fowler et al., 2008; Simon, 2010; Sundara et al., 2006; Yusa et
al., 2010). Both speakers pronounced phonologically voiceless stops with longer VOT in
English than in Czech at both times of measurement (despite the shorter duration of English
than of Czech trials, which may potentially have led to a higher speech tempo, and thus a
shortening of VOT, in English overall). The production of word-initial voiced stops was more
variable in two senses. First, both speakers realized some voiced stops in both languages with
positive and others with negative VOT (as prevoiced). Second, unlike for voiceless stops, the
production of voiced stops underwent a change after the immersion period: prevoicing
became more frequent and the VOT values became more negative. In other words, phonetic
drift was observed for our simultaneous bilinguals, corroborating previous findings of drifting
in bilinguals of other types (Sancier & Fowler, 1997; Tobin et al., 2017) and in second-
language learners (Chang, 2012, 2013). Importantly, for both speakers the production of
voiced stops changed towards the more Czech-like values not only for Czech but also for
English. In fact, in terms of the number of stops realized as prevoiced, and especially for the
younger speaker A also in terms of VOT, the drifting had greater magnitude for English than
for Czech.
Since the surface phonetic realizations of English versus Czech voiced stops, which
initially appeared to be somewhat different (as they did in a previous single-probe case study
of an early English-French bilingual child by Mack, 1990), drifted together (and their initial
potential difference largely dropped away), we conclude our bilinguals have English~Czech
voiced stop categories integrated at a more abstract level of sound representation. Such
integration may be caused by a cross-language ‘equivalence classification’ (Flege, 1995) of
the corresponding sounds (Chang, 2019, pp. 192-193). Furthermore, the drifting we observed
provides insight into underlying representation in another way. Although at the time of the
first recording the VOT values of English phonologically voiced stops and of Czech
phonologically voiceless (unaspirated) stops had largely overlapping distributions if outliers
are excluded (see Figure 1), it is clear they represent separate categories because drifting
affected only the English voiced stops.
While Tobin et al. (2017) found variation in the extent of phonetic drifting for a
heterogeneous group of late bilinguals, our two speakers displayed considerable similarity in
their productions both before and after the immersion-induced drifting. This is perhaps
expectable since they are sisters and thus have received similar input in both languages. One
indication of a difference between our speakers was in that the 16-year-old (speaker B)
seemed to maintain a somewhat clearer differentiation of the Czech and English voiced stops
than her 13-year old sister (in other words that for speaker A the phonetic drift in English
voiced stops was somewhat larger in magnitude than for her older sister). This is in line with
suggestions in previous literature (Sundara et al., 2006) that a differentiation of voiced stops
in bilinguals whose languages have different VOT settings for stops develops slowly.
The current study was designed so that the main comparison, assessing whether
phonetic drift occurred, is between the two recording times within each language.
Comparisons between English and Czech VOTs are possible (though not necessary for our
main research questions) but only with caution. The reason is twofold. First, as stated above,
there was a difference between the two language conditions in trial length, Czech trials lasting
longer than English (to provide the speakers with more time to access the lexical items in their
non-dominant language). The longer duration of Czech trials could potentially have
encouraged slower speech tempo, and thus a general lengthening of the VOT. For voiceless
stops that would mean an increased similarity between Czech and English VOT and for
voiced stops an increased difference. Even though the differences between English and Czech
VOTs are in the expected direction suggesting that no large systematic changes were induced
by the differing trial duration, it is still possible that the VOTs measured for English vs Czech
would differ somewhat if trial duration had been constant. Second, the counts of the stops
with different places of articulation measured (given above in Table 1) were only roughly
comparable between the two languages and since VOTs differ universally across places of
articulation (Cho & Ladefoged, 1999), this could potentially have introduced some difference
between the values we measured for each language. Relatedly, future research, carefully
controlling for place of articulation and having a larger data set than the one we could obtain
from our speakers, could assess the amount of drift across different places of articulation, as it
may not necessarily be the same (as it was not for the novice late second-language learners in
Chang, 2012). In addition, future research may determine whether comparable phonetic drift
occurs for stops in other positions (word-medial and -final).
This being a case study, a further limitation is that the number of participants recruited
was very small. However, also previous longitudinal studies of early bilinguals have been
case studies (Simon’s [2010] and Yang, et al’s [2015] studies both have a single participant).
This is because there is a relative scarcity of early bilinguals available for longitudinal
investigations. It is possible that the patterns of phonetic drift observed in our two speakers
(who are siblings) are typical of simultaneous bilinguals. However, further research with a
more representative sample size is necessary to determine with confidence whether this is
actually the case or not.
In summary, despite some limitations, our data from two teenage simultaneous
English-Czech bilinguals provides evidence of a phonetic drift due to a change in the ambient
linguistic environment. We show that phonetic drift can reveal cross-language connections (cf
the English and Czech voiced stops in our study), as well as separations for sounds with
similar phonetic realizations in both languages (cf the English voiced and Czech voiceless
stops in session 1 in our study). Therefore, observing phonetic drift can be informative about
the organization of phonological space in simultaneous bilinguals.
Acknowledgements
We are grateful to two anonymous reviewers for valuable comments on an earlier version of
this paper. We thank David Ryška for technical assistance.
Declaration of Conflicting Interest
The Authors declare that there is no conflict of interest.
Funding
The authors disclosed receipt of the following financial support for the research, authorship,
and/or publication of this article: This work was supported by a grant from the Czech Science
Foundation (GACR) number 18-01799S.
Notes
1. To our knowledge no published data is available for the VOT of word-initial Czech stops.
The existing research by Machač (2006) focused on stops in medial positions where the VOT
of voiceless but not of voiced stops can be determined. For the voiceless stops, Machač
(2006) provides the following values: 0.017 s for /p/, 0.020 s for /t/, and 0.032 s for /k/. For
the voiced stops, our own unpublished measurements of two speakers, pronouncing 53 Czech
isolated voiced-stop-initial words each, show that one speaker (male) always realized the
voiced stops with prevoicing, with the average VOT of -0.098 s, while the other speaker
(female) prevoiced the stops 99.6 % of the time, with prevoicing lasting -0.076 s on average.
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