Bilingual lips: Motor activation for second language word processing

Abstract

Aims and objectives:

Current research suggests that motor articulatory representations are relevant for optimal speech processing under difficult circumstances. The challenging situation of a second language (L2) listener mimics this sub-optimal condition; therefore, activation of motor brain regions to support L2 processing is expected. This study aimed to investigate if the motor system associated with speech articulators exerts an influence on processing bilingual acoustic inputs.

Methodology:

Thirty proficient bilinguals performed twice on a word-to-picture matching task: (1) while producing constant contraction of the orbicularis oris (OO) muscle interfering with the articulator’s movement and (2) while producing constant contraction of the first dorsal interosseus (index finger) muscle.

Data and analysis:

Accuracy and reaction times (RTs) were collected from the bilingual task during the experimental and control conditions. Two-way repeated measures analyses of variance were conducted to assess if constant contraction of articulators yielded a significant effect on word recognition in L1 and L2.

Findings:

Word recognition was significantly slower in L2 compared with the native language (L1) during articulator contraction. Task accuracy in L1 was marginally better during the finger muscle contraction compared with OO muscle contraction, and no difference in accuracy was found in L2. An interesting distinct speed-accuracy trade-off strategy for L1 and L2 was observed. The findings support the hypothesis of a motor system facilitatory effect on processing acoustic inputs in bilinguals.

Originality:

The role of motor components in language processing has been studied in challenging linguistic environments, but little has been done to identify its role in L2 processing. This study used an innovative behavioral strategy to interfere with articulatory muscles during word recognition.

Significance:

Our results provide evidence of motor system processing support to L2 word recognition. In addition, a bilingual tendency to sacrifice speed for accuracy in L2 compared with L1 is suggested.

Keywords

Bilingualism motor system word recognition second language processing

Introduction

Until recently, it was thought that auditory and productive speech processing occurs as two separate language systems in different areas of the brain: the sensory processing for language perception activates the superior temporal gyrus, and the motor processing for speech production activates the motor cortex. Research is suggesting an overlap as neural production processes are found to be involved in speech perception. Apparently sensory-motor integration is important for oral language perception (Di Cesare et al., 2017; Juárez et al., 2019; Sakai & Moorman, 2018; Schomers & Pulvermüller, 2016; Wilson et al., 2004); however, the exact role of the motor system in speech comprehension is still under discussion.

Empirical evidence is emerging showing that speech-related motor areas are active while listening to verbal stimuli (D’Ausilio et al., 2009; Galantucci et al., 2009; Meister et al., 2007; Repetto et al., 2013; Schomers et al., 2015; Vukovic et al., 2017). For instance, Cheung et al. (2016) recorded neural activity from the perisylvian speech cortex in participants undergoing clinical monitoring for epilepsy surgery. They found activation in the pre-central regions associated with phonation and laryngeal control while listening to speech, demonstrating that the motor cortex is engaged and plays a role in passive speech perception. Murakami et al. (2011) compared motor-evoked potential (MEP) amplitudes recorded from the orbicularis oris (OO) muscle while viewing speech-related lip movements, listening to speech, or listening to white noise while viewing visual noise (control conditions). They found that MEP amplitudes from the right OO muscle significantly increased when viewing or listening to speech, in comparison to the control condition.

Current research suggests that motor articulatory representations are relevant for optimal performance during speech processing. For example, Willems et al. (2011) found that lexical decisions for manual action verbs were faster after theta-burst stimulation (TBS) to the left premotor cortex in comparison to TBS to the right hemisphere, suggesting that processing action verbs is partly dependent on the activity of motor areas related to the planning and execution of the action named by the verb. Similarly, activation of motor brain regions simulating articulatory gestures while processing action and abstract verbs produced by human and robot speakers was found (Di Cesare et al., 2017). In addition, a facilitatory effect of primary motor cortex (M1) activation on semantic processing was confirmed by the fact that temporary disruption of the left M1 produced a delay in concrete action verb processing (Repetto et al., 2013).

The acoustic and articulatory representations necessary for language production and comprehension are connected, and this association between representations implies that the motor system is engaged during speech comprehension. Schomers et al. (2015) found that the articulatory motor cortex may have a causal effect on meaningful spoken word comprehension. In this study, immediately after applying transcranial magnetic stimulation (TMS) to the left motor cortex to either the lip or the tongue area, minimal pairs of words that started with a bilabial or an alveolar stop consonant were presented in a word-to-picture matching task. It was found that response times were shorter, and accuracy was higher when a congruent sector of the articulatory motor cortex (lip or tongue) was stimulated, suggesting facilitation of word recognition when the motor area associated with the articulator necessary for producing the word was engaged. TMS-induced disruption of the brain regions controlling the movements of the lip muscle decreased sensitivity in a syllable discrimination task (Smalle et al., 2015), and a functional magnetic resonance imaging (fMRI) study revealed that the perception of speech sounds during a listening task activates the same motor circuits involved in the articulatory process to produce the sounds (Pulvermüller et al., 2006). Specifically, researchers found that the lip and tongue motor cortex areas involved in articulatory processing were differentially activated during the perception of lip- and tongue-related phonemes, supporting the argument of motor cortex contribution to perceptual processing of speech sounds.

However, others have argued that the role of the motor cortex on the perceptual processing of speech is modulatory, and therefore, not necessarily involved in processing speech signals (Hickok et al., 2011; Hickok & Poeppel, 2004, 2007; Möttönen & Watkins, 2009; Skipper et al., 2005; Stasenko et al., 2015). For example, Arsenault and Buchsbaum (2015) found no evidence of activation in the motor cortex areas involved in the production of labial and alveolar consonants during a passive auditory perception task. This fMRI study failed to replicate Pulvermüller et al.’s (2006) results and suggests that the passive perception of speech sounds does not recruit the motor circuits involved in speech production under typical listening conditions (Hickok, 2009).

The different results could be explained by current neurocognitive models suggesting that the motor system plays an important role in speech comprehension under difficult circumstances, for example, when the speech signal undergoes external (environmental factors like noise) and/or internal (characteristics of the speaker such as accent, style, or vocal tract differences) distortions (Bartoli et al., 2013; Devlin & Aydelott, 2009; Du et al., 2014; Nuttall et al., 2017; Van Engen & Peelle, 2014). In a meta-analysis, Adank (2012) found that difficult listening conditions lead to increased activation of areas involved in speech production. Nuttall et al. (2017) supported the notion that there is activity in the motor cortex while listening to distorted speech. In this study, they found that the motor system aids speech perception under difficult listening conditions, for example, listening to motor-distorted speech or speech embedded in noise.

For a second language (L2) learner, language comprehension involves processing under challenging listening conditions due to the lack of experience with the new language sounds (Abutalebi et al., 2009; Chee et al., 2001; Costa & Sebastián-Gallés, 2014; Van Engen & Peelle, 2014), and the influence of highly overlearned selective perceptual routines of the L1 over the L2 processing (Lee & Lyster, 2017). The use of two or more languages imposes additional neurocognitive demands (Abutalebi & Green, 2016). The challenging situation of a L2 listener mimics the situation of a listener under sub-optimal conditions; therefore, activation of motor brain regions that support speech perception is expected. Schmitz et al. (2018a) found that compensatory motor activities are generated when listening to non-native speech sounds. They found that lip corticobulbar excitability increases as the perceived familiarity of the speech sound decreases, providing a neurophysiological demonstration that listening to non-native speech sounds induces greater activation of the motor system. Similarly, Callan et al. (2014) found that the perception of foreign-accented phonetic categories involves the activation of brain regions associated with speech motor control and a study with Spanish/Catalan bilinguals found evidence of the production system being causally involved in L2 speech perception (Schmitz et al., 2018b). A study using repetitive TMS (rTMS) to modulate the M1 associated with speech production, specifically the lip muscle during a bilingual (English/Spanish) word recognition task, found evidence of motor support to spoken word recognition in the L2, suggesting that M1 excitability contributes to L2 speech processing, but this effect was not found with L1 speech recognition (Barragan et al., 2022).

Some researchers hypothesized that when learning to articulate a non-native speech sound, the ventral stream projecting to frontal motor regions may provide a mechanism to store sensory representations of speech and compare them against articulatory production. This comparison may improve future productions, as stronger motor programs would support speech perception through a top-down mechanism that helps disambiguate phonological information (Du et al., 2014; Sato et al., 2009; Tourville & Guenther, 2011). There is evidence supporting the idea that motor training for new phoneme production, in addition to visual articulatory information and feedback, enhances speech comprehension (Kartushina et al., 2015; Navarra & Soto-Faraco, 2007; Schmitz et al., 2018a; Zamuner et al., 2016). These findings support the hypothesis that L2 learning requires a stronger functional connectivity between articulatory–auditory and articulatory–orosensory systems to facilitate phonetic identification (Callan et al., 2004, 2014).

Data suggest that L2 speech perception is not purely sensory or motor but involves a sensorimotor process. Wilson and Iacoboni (2006) found that motor areas are activated during non-native phoneme perception and these areas are functionally connected to the temporal sensory cortex. Supporting evidence was found in a study using diffusion tensor imaging where language learning stimulated white matter changes that enhanced sensory-motor connections (Kuhl et al., 2016). Speech perception and production develop concurrently and the link between them is present in children’s native language (L1) acquisition (Mok et al., 2019). The role of the motor system in non-native sound discrimination is observed very early during infant development. Activation in both auditory and motor brain areas is equivalent during a native and non-native phonetic discrimination task in 7-month-old infants, but by the end of the first year of life, infants’ brain activation in auditory areas for native stimuli exceeded that of non-native sounds, while the activation in motor areas was greater for non-native than native speech stimuli (Kuhl et al., 2014). Six-month-old infants from English speaking families could not differentiate between Hindi dental /d̯/ and retroflex /ɖ/ while using a flat teething toy that interfered with tongue movements; conversely, infants using a gummy teether that did not interfere with tongue movements successfully discriminated the non-native contrast (Bruderer et al., 2015). These findings suggest an important role of the motor system during L2 perception from a very early age.

In line with the bilingual research previously mentioned, this project aimed to investigate if the motor system associated with speech articulators exerts an influence on processing acoustic inputs in bilingual adults. We manipulated the position of the articulators in proficient Spanish/English bilinguals and tested if this affected their bilingual word recognition. Specifically, we tested if interfering with speech articulators’ movement yields an effect on a word recognition task, and if this interference yields a larger effect in a word recognition task in L2 compared with the L1. For this purpose, we designed a bilingual word-to-picture matching task using minimal pairs in English and Spanish. Participants performed the task while holding a spoon with their lips therefore, keeping a constant contraction of the OO muscle (experimental condition), or while holding the spoon balanced between the index and thumb fingers to produce a constant contraction of the first dorsal interosseus (FDI) muscle (control condition). If the motor system is involved in speech perception, word recognition should be affected by impeding the articulators’ free movement. In addition, the impact on performance of this condition is expected to be even more detrimental in L2 than in L1, due to the additional neurocognitive demand in L2 processing.

Method

Participants

Data were collected from 30 English/Spanish bilingual participants. The average age of participants was 37 years old (see Table 1 for participant’s demographics). Eighteen self-identified on the Language Experience and Proficiency Questionnaire (LEAP-Q) (Marian et al., 2007) as English native speakers and 12 as native Spanish speakers. This information was used to compare the average performance within participants on L1 versus L2, independently of which one was the native or the second language. Information gathered through the LEAP-Q showed that the average age of second language acquisition was 5.5 years, and all participants reported intermediate to high proficiency level on L2. The average proficiency level for L2 speaking and reading was 7 (good according to LEAP-Q scale), and for L2 understanding was 8 (very good according to LEAP-Q scale).

Table 1.

Participants’ demographics.

L1	N	Gender	Age range (years)	Mean age (years)
English	18	8 F—10 M	18–53	34
Spanish	12	8 F—4 M	23–59	40
Total	30	16 F—14 M	18–59	37

Note. Native language (L1) was determined by the participant through the Language Experience and Proficiency Questionnaire (LEAP-Q).

Stimuli

Two databases, the SUBTLEX_US corpus (Brysbaert & New, 2009) and the Clearpond-Spanish corpus (Marian et al., 2012) were consulted, in addition to input from native English and Spanish speakers, to select 40 high-frequency words in both languages (Appendix 1). Selected English and Spanish words had a frequency per million words (fpm) average above 100 fpm, which is the standard for high-frequency words (Brysbaert et al., 2018); no significant difference was found between the fpm in both languages (t₍₇₈₎ = 1.35, p = .18). These words corresponded to 20 minimal pairs, that is, pairs of words that differ in only one phonological element. Previous studies investigating neuromotor activity during speech perception have used phonemes (bilabials vs dental) and syllables discrimination tasks (e.g., Bartoli et al., 2013; D’Ausilio et al., 2009; Schmitz et al., 2018a), but little has been done with whole word discrimination. A minimal pair task allows for phoneme discrimination in the context of whole word recognition. Because the focus of this study was to engage the lip articulator muscles, the minimal pairs selected involved a difference in OO muscle contraction or movement during production, for example, “ g irl”—“ p earl” or “ f uerte”—“ s uerte” (strong—luck).

To prevent the participants from recognizing the phonological nature of the experiment, 40 filler words in each language were also included in the task. The chosen word stimuli were recorded in a sound booth by an English/Spanish bilingual female speaker. All words were embedded in white noise at a signal-to-noise ratio (SNR) of −2 db. This level of noise served to increase the difficulty of the recognition task. All 160 words (80 experimental and 80 filler) were randomly assigned to List A or List B. Each list included 20 experimental English, 20 experimental Spanish, 20 filler English, and 20 filler Spanish words. Words within each list were presented randomly.

Word-to-picture matching task

A word-to-picture matching task experiment was built and administered using PsychoPy©. Images that most closely represented each auditory stimulus were selected. Each image stimulus was placed into a grouping of four images that flashed immediately on the computer screen after the auditory stimuli was presented. Specifically, one image was the target word (e.g., girl), another corresponded to the minimal pair (e.g., pearl), a third image corresponded to a word in the same semantic category (e.g., boy), and finally, an image corresponding to an unrelated word (e.g., honey). In the word-to-picture matching task these groupings of images were displayed in a random order on the computer screen, with a number below describing the screen location (1 =left, 2 = left-center, 3 = right-center, 4 = right). Participants were instructed to choose the image that most accurately reflected the auditory word presented, using numbers 1 through 4 in the computer keyboard with the index finger of the non-dominant hand (see Figure 1 for a graphic description of the task). Performance in the task did not require a reading component as the verbal stimuli was presented auditorily and the images did not include written elements. Accuracy and reaction time (RT) were recorded.

Figure 1.

Word-to-picture matching task.

Procedure

Prior to their participation in the study, all volunteers gave written informed consent approved by California State University Los Angeles Institutional Review Board (IRB) in accordance with the Declaration of Helsinki. They completed a Handedness Questionnaire to determine hand dominance (Oldfield, 1971). Participants sat in front of a computer using headphones and performed on the word-to-picture matching task listening to List A or B (ordered counterbalanced across participants) of English/Spanish words. Participants were instructed to use their non-dominant hand when choosing a response on the keyboard.

Participants performed twice (order counterbalanced across participants) on the word-to-picture matching task previously described: 1. While holding the handle of a plastic spoon with an additional weight of 0.2 ounces with the lips (one US quarter). They were instructed to keep the spoon as parallel to the ground as possible to prevent the coin from falling, by holding the spoon with the lips, not with the tongue or teeth. This produced a constant contraction of the OO muscle during the task performance. 2. While holding a plastic spoon with an additional weight of 1.4 ounces (seven US quarters) between the index finger and the thumb of the dominant hand. Participants were instructed to use the thumb only for stabilizing the spoon, but all the weight should be supported with the index finger. This produced a constant contraction of the FDI muscle. Performing on the word-to-picture matching task while holding the spoon with the lips was considered the experimental condition and holding the spoon with the finger was considered the control condition. Participants were randomly assigned to begin the experiment either holding the spoon with their lips or with their finger.

The experimental and control conditions were presented at least 45 minutes apart. During the 45-minute break, participants completed the LEAP-Q form to provide information about their bilingual language background (LEAP-Q; Marian et al., 2007).

Results

Accuracy and RTs were collected from the bilingual word-to-picture matching task during the experimental (contraction of OO muscle) and control (contraction of FDI muscle) conditions and were recorded using PsychoPy© software. Based on the information provided by each participant through the LEAP-Q, performance data were divided by language, native (L1) and second (L2) language for statistical analysis.

Reaction time

RT was collected as the time elapse between listening to the word stimulus and choosing on the computer’s keyboard the picture presented on the screen. Average RT of correct responses per participant was calculated. A two-way repeated measures analysis of variance (rmANOVA) was conducted to assess if constant contraction of articulators yielded a significant effect of time necessary for identification of words in L1 and L2. The analyzed factors were language (L1 vs L2) and condition (experimental vs control).

The two-way rmANOVA on RT revealed a significant main effect of language (F_(1,29) = 6.62, p = .015), but not for condition (F_(1,29) = 0.49, p = .48). However, a significant interaction language-condition effect was found (F_(1,29) = 5.43, p = .02). The interaction effect is explained by significant slower responses in L2 compared with L1 in the experimental condition (post hoc t tests using Bonferroni adjustment t₍₂₉₎ = −3.54, p = .001). This shows that for L2, but not for L1, OO contraction produced slower responses compared with RT during FDI contraction (Figure 2).

Figure 2.

Results for reaction time (RT).

Altogether, participants’ RTs were similar in L1 regardless of whether there was contraction of the OO or FDI muscle. Interestingly, participant’s responses in L2 were slower during OO contraction compared with L1, suggesting an articulator muscle interference effect only in L2.

Accuracy

Accuracy scores were collected as number of correct responses on the word-to-picture-matching task. Participants performed substantially better than chance level (chance level = 5 correct responses out of 20 possible correct). A two-way rmANOVA was conducted to assess if constant contraction of articulators yielded a significant effect on the identification of words in L1 and L2. The analyzed factors were language (L1 vs L2) and condition (experimental vs control). The two-way rmANOVA revealed no significant main effect for language (F_(1,29) = 4.07, p = .057), condition (F_(1,29) = 3.81, p = .06) or interaction effect (F_(1,29) = 3.80, p = .06).

Considering the closeness of main effects and interaction effect to significance criterion, pairwise comparison controlling for Type II error using Holm’s sequential Bonferroni adjustment were conducted and revealed a significant difference between accuracy in L1 and L2 (t₍₂₉₎ = 2.75, p = .01) due to a better performance in L1 during the control condition. L1 accuracy was significantly higher in the control condition than in the experimental condition (t₍₂₉₎ = 2.84, p = .008), but this difference was not found in L2 (t₍₂₉₎ = 0.59, p = .56) (Figure 3). This result reveals an interesting trend suggesting a better performance in L1 than L2, and an effect of OO muscle contraction on L1.

Figure 3.

Results for accuracy.

Discussion

This study evaluated the role of the motor system associated with speech articulators of bilingual adults in processing acoustic inputs. More specifically, we interfered with the movement of speech articulators and assessed its effect on a word recognition task in the native and second language of proficient English/Spanish bilinguals. To the extent that the motor system supports language processing under difficult circumstances (Adank, 2012; Bartoli et al., 2013; Nuttall et al., 2016), interference with movements of the OO muscle was expected to have a detrimental effect on a word recognition task. Furthermore, we expected this effect to be more pervasive in L2 compared with L1, as the L1 influences perception of the L2 sound system and, even after years of exposure to L2, listeners may struggle with the perception of non-native contrasts (Barrios et al., 2016).

The significant two-way interaction effect between language (L1 vs L2) and condition (experimental vs control) on RT provides evidence of the motor system processing support to L2 word recognition. Participants were significantly slower when performing on L2 during the experimental condition, showing that constant contraction of the OO muscle interfered with L2 word recognition. This effect suggests that greater cognitive effort is needed to process words in a less familiar language (Abutalebi et al., 2009; Hernandez, 2009; Hernandez & Meschyan, 2006; Krizman et al., 2017; Rodriguez-Fornells et al., 2005; Xue et al., 2004), and activation of the motor system is evident when there is added difficulty in the speech perception task or a higher processing load (Stasenko et al., 2015). This result is in line with Nuttall et al.’s (2016) finding that the activation of the motor system increases with the difficulty of the perceptual task. It provides additional support to neurocognitive models arguing that the activation of the motor system during speech perception supports a top-down processing of the incoming stimuli, where a production-base model of the input is activated to support processing under sub-optimal listening conditions (Adank, 2012; Devlin & Aydelott, 2009; Du et al., 2014; Nuttall et al., 2016; Sato et al., 2011; Stasenko et al., 2015; Van Engen & Peelle, 2014).

The RT difference in L2 was found only in the experimental condition when the OO muscle was active, not during activation of the FDI muscle (control condition). This suggests that the motor system specifically associated with the articulators is engaged during speech comprehension. This result is congruent with Möttönen and Watkins’ (2009) findings that TMS-induced disruption of the lip associated motor cortex impaired the discrimination accuracy of /pa/-/ta/ syllables, while the disruption of the hand-associated motor cortex had no effect on the syllable discrimination. In addition, the difference in condition (experimental vs control) effect was found in L2 only, indicating that task characteristics (e.g., difficulty level) are not main factors contributing to the results.

The two-way interaction effect on accuracy suggests better performance on L1 compared with L2 during FDI muscle contraction, although this effect was marginally significant (p = .06). Not reaching the significance criterion may reflect an accuracy ceiling effect due to the ease of the task. The minimal pairs used included high-frequency words that should be easy to recognize for intermediate-to-highly proficient bilinguals. To add difficulty to the task, the words were embedded in white noise following previous research demonstrating that bilingual perception of linguistic stimuli in noise is more challenging than monolingual perception (Krizman et al., 2017); however, an SNR of −2 dB is considered an intermediate-to-weak noise level (Du et al., 2014; Lacross et al., 2016). Nevertheless, the results in accuracy showed an interesting pattern: L1 performance decreased during the experimental condition (performing during constant OO muscle contraction) compared with the control condition (performing during FDI muscle contraction). This difference was not observed in L2 performance, where accuracy for experimental and control conditions was similar. We expected the opposite result, assuming that performance on L2 would be more challenging and, therefore, more dependent on motor support.

When analyzing accuracy and RT results combined, the unexpected accuracy trend can be understood from the perspective of a distinct speed-accuracy trade-off strategy (Boldini et al., 2004; Heitz, 2014; Meyer et al., 1988). For L1, RT was similar during control and experimental conditions, but performance was less accurate during the experimental than the control condition. Conversely, for L2, accuracy was similar for control and experimental conditions, but responses were slower during the experimental condition. Speed-accuracy trade-off is particularly salient in bilinguals (Aycicegi & Peynircioglu, 2002; Chennupatu, 2018; Latash & Mikaelian, 2010; Wu et al., 2019). For example, in a study where two groups of children, monolingual and bilingual, performed in cognitive control tasks, the results revealed that bilinguals optimized their performance by choosing a strategy, either boosting their response times at the cost of accuracy or improving their accuracy by slowing down their performance. Monolinguals did not use this trade-off strategy and their performance did not show any relationship between speed and accuracy (Struys et al., 2018). Our bilingual participants apparently used a distinct L1 L2 trade-off strategy for L1 and L2 during the speech articulator interference. In L1, processing speed was constant, but accuracy was affected. In L2, accuracy remained equivalent, but speed was slower. This result is in line with Chennupatu (2018) findings, where bilingual individuals were more likely to trade-off RT (slower responses) in favor of accuracy while performing on a minimal pair discrimination task in L2. The distinct trade-off strategy suggests differences in cognitive processing of L1 and L2 in bilinguals.

The findings in this study support the assumption of motor system association with the activation of speech articulators for processing acoustic inputs in bilingual adults. Constant activation of the OO muscle while performing on a word recognition task influenced response speed on L2 where RTs were significantly slower. Future studies may find more conclusive results related to accuracy by controlling for task difficulty relative to participant’s proficiency, preventing ceiling effects on performance. Although our results were not conclusive in finding the motor system to be more supportive of L2 processing than L1 as expected, a distinct speed-accuracy trade-off strategy was observed. We found an apparent strategy to focus on speed at the cost of accuracy on L1, while focusing on accuracy at the cost of speed in L2. It is possible that bilingual individuals display a greater tendency to sacrifice speed for accuracy in L2 compared with L1.

Footnotes

Appendix

Appendix 1

Spanish minimal pairs		English minimal pairs
bar	mar	band	sand
bala	sala	bees	cheese
cabina	camina	bell	hell
boca	loca	bake	wake
boda	moda	book	look
cama	cara	bug	rug
camino	casino	can	man
cola	copa	money	honey
via	dia	pearl	girl
mago	lago	toy	boy
fuego	juego	fall	ball
fuente	puente	mad	sad
elefante	elegante	nurse	purse
fuerte	suerte	pain	rain
ropa	rosa	pet	jet
rubia	lluvia	dark	park
papa	tapa	race	face
fiesta	siesta	pie	tie
uva	uña	pan	van
piña	niña	sea	tea

Acknowledgements

The authors thank the participants in the study.

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research was supported by the Awards and Leaves Committee at California State University, Los Angeles [Minigrant 2020/2021].

ORCID iD

Beatriz Barragan

Author biographies

Beatriz Barragan is an associate professor in the Department of Audiology & Speech-Language Pathology at A.T. Still University-Arizona School of Health Sciences. She is a bilingual (Spanish and English) researcher interested in the neurobiology of bilingualism, specifically the motor component of second language processing.

Elizabeth Alvarado is an AuD. student in the Department of Communication Disorders at California State University, Los Angeles.

Sandy Cordon is an AuD. student in the Department of Communication Disorders and Sciences at California State University, Northridge.

Jacqueline Samols is a MS. student in the School of Communication Sciences and Disorders at Pacific University, Oregon.

Michael Zandona is an AuD. student in the Department of Communication Sceinces & Disorders at University of South Florida.

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