# Dichotic Training Modulates Phonetic Feature Processing in Late English Learners: Evidence from Categorical Perception and the Mismatch Negativity

Margot Bouhon, Anna Fiveash, Jade Charron, Agathe Foureix, Barbara

Tillmann, Nathalie Bedoin

► To cite this version:

Margot Bouhon, Anna Fiveash, Jade Charron, Agathe Foureix, Barbara Tillmann, et al. Dichotic Training Modulates Phonetic Feature Processing in Late English Learners: Evidence from Categorical Perception and the Mismatch Negativity. Journal of the Acoustical Society of America, 2025, 157 (5), pp.3907-3921. 10.1121/10.0036725. hal-05390783

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Dichotic Training Modulates Phonetic Feature Processing in Late English Learners: Evidence

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from Categorical Perception and the Mismatch Negativity

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Margot Bouhon<sup>1,2,3,5</sup>, Anna Fiveash<sup>6, 7</sup>, Jade Charron<sup>4</sup>, Agathe Foureix<sup>4</sup>, Barbara Tillmann<sup>2,7</sup>

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Nathalie Bedoin<sup>3,4</sup>

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<sup>1</sup> Laboratoire de Psychologie Sociale et Cognitive (LAPSCO), CNRS-UMR 6024, Université

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Clermont-Auvergne, Clermont-Ferrand, France

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<sup>2</sup> Centre de Recherche en Neurosciences de Lyon, Equipe Cognition Auditive et

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Psychoacoustique, CNRS-UMR 5292, Inserm U 1028, Université Lyon 1, Bron, France

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<sup>3</sup> Centre de Recherche en Neurosciences de Lyon, Equipe Trajectoires, CNRS-UMR 5292,

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Inserm U 1028, Université Lyon 1, Bron, France

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<sup>4</sup> Université Lyon 2, Lyon, France

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<sup>5</sup> Contentsquare – Contentsquare Foundation, Paris, France

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<sup>6</sup> The MARCS Institute for Brain, Behaviour and Development, Western Sydney University,

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Sydney, Australia

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<sup>7</sup> Université Bourgogne Europe, CNRS, LEAD UMR5022, 21000, Dijon, France

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Corresponding author: Dr. Margot Bouhon, Laboratoire de Psychologie Sociale et Cognitive

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(LAPSCO), UMR 6024, CNRS & Université Clermont-Auvergne, Clermont-Ferrand, France.

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Email: [bouhonmargot@gmail.com](mailto:bouhonmargot@gmail.com)

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In English, voiceless stop consonants (i.e., /p-t-k/) have long Voice Onset Times (VOT), and voiced stop consonants (i.e., /b-d-g/) have short VOTs. **In French, voiceless stop consonants have short VOTs while voiced stop consonants have pre-lag VOTs, which can make late second language (L2) learning of English difficult.** The Asymmetric Sampling in Time (AST) model proposes that slow and fast cerebral rhythms dominate in the auditory cortex of right and left hemispheres (RH, LH), respectively, and preferentially support processing of long and short speech events. **Our study extends the application of this model to sub-phonemic levels, where short VOTs were presented to the right ear (stimulating the LH), and long VOTs were presented to the left ear (dichotic stimulation). Pre/post-tests assessed categorical perception performance in adults trained dichotically, binaurally, or without training.** Consonant perception improved in dichotic and binaural groups, with generalization of training only in the dichotic group (Experiment 1). Following dichotic training, the Mismatch Negativity amplitude increased for voiced English deviants, and hemispheric dominance shifted appropriately for voiceless deviants (Experiment 2). These findings demonstrate that perceptual training grounded in an AST framework can induce phonological perception changes in late English learners, suggesting promising directions for L2 perceptual training.

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Keywords: L2 learning, dichotic listening, VOT, MMN, hemispheric asymmetry

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# I. INTRODUCTION

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Speech perception in a second language (L2) can present significant challenges for late
learners, necessitating substantial modifications to already developed speech processing
circuits (Luk et al., 2020). Recent advancements in neuroscience suggest that the difficulty
observed for adults learning an L2 may not be based primarily on a decline in brain plasticity
with age. Instead,–adult learners’ challenges are more likely influenced by motivational
factors (DeKeyser & Larson-Hall, 2005), suboptimal learning conditions (Kang et al., 2021),
and insufficient input frequency (Ellis, 2002). In the case of French speakers learning English,
difficulties may also arise because the assimilation of new phonemes to L1 phonological
categories are initially made without clear perception of phonetic differences.

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## A. French speakers learning English voicing contrasts

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For French speakers learning English, two additional sources of phonological errors are anticipated. First, the shared grapheme-phoneme correspondences for consonants between the two languages (e.g., P-/p/, B-/b/) may mask the phonetic variations between the two languages, which include differences in acoustic and articulatory properties. Consequently, when reading English words, French speakers are likely to interpret them using native phonetic contrasts, reinforcing the incorrect assumption that English and French consonants exhibit phonetic similarity. Second, late learners tend to assimilate L2 sounds to the phonological category that is phonetically closest to the related L1 category (Grimaldi et al., 2014), potentially leading to perceptual and production errors.

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In this context, the distinction between English voiced and voiceless consonants poses a particular challenge for French-speaking English learners. The present study focuses on the voicing contrast, which primarily depends on Voice-Onset-Time (VOT) in both languages, albeit in distinct ways. VOT is defined as the duration between the release of a stop consonant (the burst) and the onset of vocal fold vibration (the onset of voicing). In English Consonant-
66 Vowel (CV) syllables, voiced stop consonants (/b-d-g/) have a short positive VOT, while 67 aspirated voiceless stop consonants (/p-t-k/) are characterized by a long positive VOT 68 (phonetically, [pʰ-tʰ-kʰ]). In contrast, French voiced stop consonants are marked by a pre-lag 69 VOT, while voiceless stop consonants have a short positive VOT ([p-t-k]), similar to the VOT 70 pattern found in English voiced stops.

71 Consequently, French learners experience what is referred to as 'single category 72 assimilation' within the Perceptual Assimilation Model (PAM-L2; Best & Tyler, 2007) 73 and a 'new scenario' in the Second Linguistic Perception model (L2LP; Escudero, 2009; 74 van Leussen & Escudero, 2015). In these models, the English voicing contrasts (L2) risk 75 being initially assimilated into a single L1 category. For instance, the English sounds [pʰ] 76 and [b] may be perceived as atypical and typical exemplars of the L1 /p/ category, 77 respectively. L2 perception has been suggested to improve when learners shift toward a 78 'two-category assimilation', according to the PAM-L2 model (Tyler, 2019), or a 'similar 79 scenario' in the L2LP framework, wherein tokens such as [pʰ] and [b] are assimilated 80 into distinct L1 categories (i.e., /p/ and /b/). However, ambiguity arising from differences in 81 the associations between short vs. long VOTs and voiced vs. voiceless consonants in French 82 and English may hinder learners' progression to this advanced stage of L2 perception. 83 Perceptual training targeting specific phonological contrasts has been put forward as a method 84 to aid learners in developing L2 phonological categories that reflect phonetic differences in 85 the L2.

86 The revised Speech Learning Model (SLM-r; Flege & Bohn, 2021) posits that the 87 capacity to establish new L2 phonetic-phonemic associations persists throughout the lifespan, 88 contingent upon factors such as the acoustic similarity between L1 and L2 sounds, the 89 precision of L1 categories, and the quantity of authentic L2 input received (Ellis, 2002). The 90 developmental process from naïve non-native to native-like L2 speech perception is the object
of study of the L2LP model (van Leussen & Escudero, 2015). Similarly, the PAM-L2 (Best & Tyler, 2007) hypothesizes that late learners can attain heightened sensitivity to L2 phonological contrasts, especially following targeted training emphasizing specific phonetic distinctions between L2 phonemes.

The training program employed in our study was grounded in these theoretical frameworks, as well as the neurolinguistic Asymmetric Sampling in Time model (AST; Poeppel, 2003).

## B. Extending the AST model to phonetic features using dichotic training

The AST model posits that speech perception involves bilateral non-primary auditory cortices, with preferential hemispheric processing depending on frequency (Boemio et al., 2005; Teng et al., 2016). Temporal processing of speech is suggested to be governed by the synchronization of rapid, left-hemisphere-dominant endogenous neural oscillations for the processing of short linguistic units (phonemes), and slower, right-hemisphere-dominant neural oscillations for the processing of longer linguistic units (syllables) (Oderbolz et al., 2025).

The current study was based on this hemispheric specialization, with the hypothesis that perceptual training involving dichotic presentation of English stop consonants would improve French learners' ability to identify and discriminate English voiced and voiceless stop consonants. This training method involves presenting stimuli to only one ear to specifically stimulate the auditory cortex in the left hemisphere (LH) or right hemisphere (RH). Functional Magnetic Resonance Imaging (fMRI) data have demonstrated that stimuli presented to the right ear specifically enhances LH activation, while stimuli presented to the left ear specifically enhances RH activation (Stefanatos et al., 2008). Consistently, behavioral dichotic listening experiments have shown that right-handed individuals typically exhibit a Right Ear Advantage (REA): they recall more the
words presented to the right ear than those presented to the left ear, when two words were
simultaneously presented to the left and right ears. The REA is suggested to reflect both the
strong contralateral relationship between the ears and the auditory cortices, and the
predominant involvement of the LH in phonological processing (Hugdahl & Wester, 1992;
Kimura, 1967).

It is important to note that the contrast between short and long VOTs examined in the
current study does not align precisely to the distinction between short events (phonemes) and
long events (syllables or prosodic units) described in the AST model. Therefore, our
hypothesis entails an additional theoretical implication. Specifically, if dichotic training leads
to a greater improvement in the perception of the English voicing contrast compared to
binaural training (control condition), this would provide support for extending the AST model
to sub-phonemic levels.

This proposed extension is corroborated by previous dichotic training studies, as
well as by dichotic listening research testing hemispheric asymmetry in the perception of
phonetic features, including temporal features. For example, Bouhon et al. (2023) showed
improved perception of duration as a phonological cue distinguishing short and long English
vowels in a proof-of-concept study. In this study, perceptual training exercises were designed
to target rapid or slow sampling skills, depending on vowel duration. Building on this
framework, in the current study, it was hypothesized that amplifying hemisphere-specific
processing would improve sensitivity to—and/or awareness of—the phonetic features
distinguishing English voiced and voiceless stop consonants.

Furthermore, dichotic listening experiments involving concurrent words differing by
only one phonetic feature (voicing of their initial consonants) have revealed divergent
hemispheric asymmetries between English (Rimol et al., 2006) and French (Bedoin et al.,
2010), consistent with the application of the AST framework to sub-phonemic levels for VOT
processing. For example, in English-speaking participants, the REA decreased when a
voiceless stop consonant (i.e., long VOT) was presented to the left ear and a voiced stop
consonant (i.e., short VOT) was presented to the right ear. In contrast, in French
speakers, the REA decreased when a voiced stop consonant was presented to the left ear
and a voiceless stop consonant was presented to the right ear. For both languages, these
findings suggest RH lateralization for long VOTs. Moreover, for word pairs differing by a
single phonetic feature, the REA was higher if this feature was associated with brief acoustic
cues, which is the case for place of articulation, supporting LH lateralization for short
phonetic features (Studdert-Kennedy & Shankweiler, 1970). The aim of the current study was
to test whether dichotic training can improve perception at the sub-phonemic level, by
investigating the processing of English VOT. This hypothesis is consistent with an extension
of the AST model to the sub-phonemic level, in line with the AST prediction that the auditory
cortex is particularly sensitive to sound contours, including VOTs (Eggermont, 2001).

C. A training program targeting the learning of sub-phonemic rules

To optimize hemispheric recruitment for phonetic analysis, the LH and RH were trained
separately using the current perceptual program. This training harnessed hemispheric
specialization to enable better processing of voiced and voiceless English stop consonants
based on their VOT duration. It was hypothesized that dichotic training would lead to greater
improvement than binaural training in the identification and discrimination of English CVs
(as determined by their voicing features).

The perceptual training program used in the previous proof-of-concept study resulted in
greater accuracy for the production of length differences between short /i/ versus long /i:/
vowels after dichotic training compared to binaural training, for both dyslexic and non-
dyslexic French-speaking adults learning English (Bouhon et al., 2023). This outcome was
interpreted as evidence that trained perception skills transferred to L2 production.
In the present study, trained consonants (/p-b/, /k-g/) were compared against untrained consonants (/t-d/), to determine whether sub-phonemic rules were acquired and generalized to untrained items. This hypothesis aligns with the featural approach (de Jong et al., 2009; Olson, 2019), which suggests that L2 learners can master new sub-phonemic components and rules. Evidence of generalization to untrained L2 phonemes would support this approach, in contrast to the segmental perspective (Flege & Bohn, 2021), which asserts that each phoneme must be specifically trained to be learned.

The goal of the current study was to investigate whether L2 perception of sub-phonemic features could be enhanced using principles outlined in the AST model. Three groups were recruited to investigate this question: (a) a control group who received no training, (b) a group who completed the training with binaural stimulation, and (c) a group who completed the training with dichotic stimulation. Categorical perception tests were administered twice to all groups. To ensure test-retest reliability and establish a baseline, the control group completed the categorical perception tests at two time points without training in between. It was predicted that both the binaural and dichotic stimulation groups would show an improvement in English voicing perception (measured through the categorical perception tests) after the perceptual training program. However, it was hypothesized that dichotic stimulation (i.e., lateralized presentation) of voiced and voiceless English consonants would facilitate sub-phonemic rule learning, resulting in enhanced categorical perception of both trained and untrained consonants (Experiment 1). To further investigate the effect of dichotic training on phonological perception, phoneme discrimination was assessed in the dichotic listening group with the Mismatch-Negativity (MMN) response in an oddball electroencephalographic (EEG) paradigm (Experiment 2). The MMN amplitude was predicted to increase following dichotic training, indicating that listeners developed preattentional sensitivity to the English voicing contrast.
## II. EXPERIMENT 1: BEHAVIORAL EVALUATION OF THE TRAINING PROGRAM

### A. Methods

#### 1. Participants

Sixty monolingual native French speakers recruited from French Universities participated: 20 were enrolled in the Dichotic Group ($M_{age} = 21.50$ years, $SD = 2.60$, 18 females), 20 in the Binaural Group ($M_{age} = 21.60$ years, $SD = 2.80$, 16 females), and 20 in the Untrained Group ($M_{age} = 22.30$ years, $SD = 1.90$, 16 females). The sample size was consistent with previous studies in this field (e.g., Grenon et al., 2019; Tamminen et al., 2015; Ylinen et al., 2010). Participants were selected based on their low-intermediate proficiency in English, not exceeding the B2 level (Common European Framework of Reference for Languages, CECRL). All were right-handed ($\ge 80\%$ 'right hand' responses on the Edinburgh Handedness Inventory; Oldfield, 1971) and exhibited a REA for processing short phonetic features.

REA was signaled by more recalled words from the right ear than from the left ear (e.g., /tas/, for /pas/-/tas/), in a dichotic listening test where the two presented words only differed by place of articulation (Bedoin et al., 2010). A REA was interpreted as indicative of LH dominance for processing short phonetic cues. All participants reported normal hearing, normal or corrected-to-normal vision, and no history of neurological, psychiatric or language-related disorders, nor any childhood learning disabilities. The study was approved by the French national ethics committee. Participants gave informed consent after the procedure had been explained to them. As compensation, they received books and board games.

#### 2. Stimuli

a. Training. A total of 172 English words beginning with /p/, /t/, /k/ or /g/ were used to create minimal (e.g., pad-bad, 69%) and **near-minimal** (e.g., gaze-case, 31%) pairs. Two female and
215 two male speakers with a standard British accent produced the words **and one version of**
216 **each was randomly selected**. Each word was illustrated with 5 different Creative Common
217 licensed images (860 images in total), **one for each presentation during the training**.

218 *b. Testing sessions*. English continua (from /ki/ to /gi/, and from /ti/ to /di/) were constructed
219 using Praat software (Boersma & Weenink, 2016), by systematically varying the VOT of
220 consonants from 0 ms to +60 ms in 10 ms increments, resulting in seven stimuli per
221 continuum (Figure 1). **Two consonant pairs that differed by place of articulation were
222 included, as such variations may influence the categorization of voicing contrasts (Benki,
223 2001).** The syllables were produced by one of the two males described above. The vowel /i:/
224 was selected instead of the more traditional /a/ in CV syllables, because it provided a clearer
225 context for isolating the effect of VOT duration from other voicing cues. The /i:/ vowel is
226 characterized by relatively stable formants over time (Hillenbrand et al., 1995), which
227 facilitates the examination of purely temporal processing (VOT). **The /ki/-/gi/ continuum
228 was utilized to assess the learning effect, while the /ti/-/di/ continuum was utilized to
229 assess potential transfer effects.**

<figure><img src="image_2.png" /></figure>

230 Figure 1. Oscillograms and spectrograms of three examples of syllables along the English
231 /di/-/ti/ continuum, and the duration of their VOT in ms, from typical /di/ (left), to typical /ti/
232 (right).

234 3. Procedure
a. General procedure. All three groups participated in a **Pre-test/Post-test design** over seven consecutive days (see Figure 2). During the testing sessions (Days 1 and 7), the categorical perception of English consonants /k/, /g/, /t/, and /d/ was assessed using stimuli presented binaurally to participants who were seated in a sound attenuated room and wore headphones (Beyerdynamic DT 770 Pro). They responded by pressing designated computer keys. **From Days 2 to 6, the participants in the Dichotic and Binaural training groups were instructed to complete the training program independently at home, ensuring that the right earphone was placed in the right ear and the left earphone in the left ear.** To monitor compliance and ensure accurate training, participants were contacted daily. In the Dichotic group, participants were not told of the lateralized presentation of stimuli. The program was structured so that English words beginning with /g/ or /b/ (i.e., voiced stop consonants, short VOT) were presented to the right ear, while English words beginning with /k/ or /p/ (i.e., voiceless stop consonants, long VOT) were presented to the left ear, with white noise competing in the other ear. In the binaural group, the same word was presented in stereo to both ears. **The Untrained group did not undergo any training.** As shown in Figure 2, categorical perception was also evaluated for French phonemes. The expected lack of impact of English training on French phoneme categorization was observed (pre-/post-test comparison), and this result will not be further discussed for the sake of brevity.

<table><thead><tr><th>Day 1 (Pre-test)<br>Testing session</th><th>Days 2 to 6<br>Training</th><th>Day 7 (Post-test)<br>Testing session</th></tr></thead><tbody><tr><td><strong>Categorical Perception</strong><br>In French<br>4 tests: Identification /ki-gi/ + /ti-di/<br>Discrimination /ki-gi/ + /ti-di/<br><br><strong>In English</strong><br>4 tests: Identification /ki-gi/ + /ti-di/<br>Discrimination /ki-gi/ + /ti-di/<br><br><strong>EEG recording (Experiment 2 – Dichotic training)</strong><br>In French<br>2 blocks: /ki/ deviant<br>/gi/ deviant<br><br><strong>In English</strong><br>2 blocks: /ki/ deviant<br>/gi/ deviant</td><td><strong>Dichotic training</strong><br>/k-g/ - /p-b/ in English<br>Vocabulary learning<br>Minimal pairs judgment (forced choice)<br><br><strong>or</strong><br><strong>Binaural training</strong><br>/k-g/ - /p-b/ in English<br>Vocabulary learning<br>Minimal pairs judgment (forced choice)<br><br><strong>or</strong><br><strong>Control – No training</strong></td><td><strong>Categorical Perception</strong><br>In French<br>4 tests: Identification /ki-gi/ + /ti-di/<br>Discrimination /ki-gi/ + /ti-di/<br><br><strong>In English</strong><br>4 tests: Identification /ki-gi/ + /ti-di/<br>Discrimination /ki-gi/ + /ti-di/<br><br><strong>EEG recording (Experiment 2 – Dichotic training)</strong><br>In French<br>2 blocks: /ki/ deviant<br>/gi/ deviant<br><br><strong>In English</strong><br>2 blocks: /ki/ deviant<br>/gi/ deviant</td></tr></tbody></table>
Figure 2. General procedure of Experiment 1 and Experiment 2, with Pretest-Training-Posttest design. Note. Results for the French phonemes (in grey) are not presented in this article.

b. Training. The training program focused on the English voicing contrast in /k-g/ and /p-b/, and was developed in accordance with the principles of High Variability Phonetic Training (HVPT) (e.g., Bradlow et al., 1999; Grenon et al., 2019; Saito et al., 2022; Strange & Dittman, 1984). Based on these principles, the program incorporated the following elements: (1) various exercises, lexical and vocalic contexts, and speaker voices; (2) the presentation of minimal and near-minimal pairs; (3) trial-by-trial feedback; (4) simultaneous auditory and visual stimulation; (5) incentives aimed at increasing the participants' vocabulary; and (6) engaging content through the use of numerous words and appealing images. Furthermore, each training day focused on a single pair of consonants, with /k-g/ targeted on Days 2 and 6 and /p-b/ on Days 3 and 5. The two words of (near-)minimal pairs were processed within the same day, facilitating the learners' experience of phonetic features in L2 phonemes, as proposed by Tyler (2019). Each word was presented twice per session, and new words were introduced daily.

Three types of exercises were proposed from Days 2 to 6 (Figure 3). Every training day (except Day 4) began with a lexical learning exercise: participants listened to an English word accompanied by its spelling, French translation, and a picture illustrating its meaning. Then, a spelling judgement task was proposed on these words: participants listened to a word and chose the correct spelling from two options on the screen, with a picture aiding their decision. On Day 4, two judgement tasks were administered, one involving a forced-choice between two written words and the other between two images, both based on the words learned on Days 2 and 3.
<figure><img src="image_3.png" /></figure>

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279 **Figure 3.** Examples of stimuli in the perceptual training program.

280 **Picture credits:** bottom left and right, via PxHere; bottom middle, by Piotr Siedlecki
281 via PublicDomainPictures.net; Top right: by ShannonShort via Pixabay.

282 **c. Testing sessions.** In both pre- and post-tests, categorical perception was evaluated using a discrimination task followed by an identification task, as outlined by Fugate (2013). Both 283 tasks commenced with stimuli from the /ki-gi/ continuum, followed by stimuli from the /ti-di/ 284 continuum, in order to minimize potential contamination of the trained pair. Each task began 285 with ten familiarization trials. No feedback was provided. 286

287 In the discrimination task, participants were required to determine whether the two 288 stimuli in each trial, separated with an interstimulus interval (ISI) of 24 ms, were perceived as 289 ‘same’ or ‘different’, as quickly as possible. Each block contained 130 trials (50 ‘different’, 290 70 ‘same’). The task lasted 10 minutes.

291 In the identification task, participants listened to and categorized each of the 140 stimuli 292 as /ki/ or /gi/ in the first block and as /ti/ or /di/ in the second block, by pressing one of two 293 response keys. Each block included 10 repetitions of each of the seven stimuli, presented in a 294 randomized order. The task lasted 5 minutes.
295 4. Data analyses

296 Discrimination responses were converted into a *d'* sensitivity index following the procedure 297 described in Macmillan and Creelman (2005). The category boundary was defined by the 298 discrimination peak along the VOT continuum for each participant (e.g., VOT+10 if it 299 occurred at the 0/+20 ms VOT pair). We chose to evaluate only the peak as it provides 300 information on both the position of the boundary and its accuracy. **The rest of the 301 discrimination curve seemed less relevant if no comparison was made between observed 302 and predicted perception, or if we are looking for an allophonic perception.** Consistent 303 with previous research (Theodore et al., 2009), this boundary varied according to the place of 304 articulation, and, on average, was observed for each group at VOT+10 for /ki-gi/ and 305 VOT+20 for /ti-di/ (Figures 3, 4 and 5).

306 The identification scores for each participant were calculated as the mean of /ki/ or /ti/ 307 responses for each stimulus. Categorical precision was quantified by the slope of the 308 psychometric function using Matlab's Palamedes toolbox (Kingdom & Prins, 2010) and the 309 PALPFML_Fit function. The latter adjusts the threshold (alpha) and slope (beta) parameters 310 of a logistic function to the identification data. The VOT corresponding to 50% /ki/ or /ti/ 311 responses was determined for each participant and regarded as the categorical boundary.

312 For statistical analysis, a significance threshold of *p* ≤ .05 was applied and effect sizes 313 were calculated using partial eta-squared (ηₚ²) or Cohen's *d* (Cohen, 1988).

314 B. Results

315 1. Pre-training results

316 Three ANOVAs were conducted to assess initial group differences and establish baseline 317 performance, with Pair (/ki-gi/, /ti-di/) as a within-subject factor and Group (untrained, 318 dichotic, binaural) as a between-subjects factor. Analyses focused on the magnitude of the 319 discrimination peaks (*d*'), identification slopes and boundaries **in the pre-test data**.
The analysis revealed a significant main effect of Group on *d'*, F(2, 114) = 3.96, *p* =
.022, ηₚ² = 0.06, indicating significantly higher sensitivity in the untrained group (M = 1.89,
SD = 1.00) compared to the binaural group (M = 1.29, SD = 1.06), t(77.72) = 2.61, *p* = .011, *d*
= 0.58 at pre-test. The untrained group and the dichotic group (M = 1.68, SD = 0.80) did not
significantly differ, t(74.28) = 1.14, *p* = .258. **There was no significant difference between
the two trained groups at baseline, t(72.32) = 1.77, *p* = .080.** There was no main effect of
Pair (*F* < 1), nor Group × Pair interaction (*F* < 1).

The identification boundary was higher for /ti-di/ ($M_{VOT}$ = +16.99 ms) than for /ki-gi/
($M_{VOT}$ = +12.52 ms), as indicated by a significant main effect of Pair, $F(1, 114) = 14.00, p <$
.001, $η_p^2$ = 0.11. This result was consistent with the location of the discrimination peaks.

Given the higher initial *d'* for discrimination observed in the untrained group, we
refrained from conducting further ANOVAs including this group as a **control**<fnref n="1" />. There were no
significant differences between the two trained groups at baseline for the discrimination peak
magnitude, identification slope or boundary values (all *p* > .47). **However, the greater visual
variability observed in the binaural group's performance compared to the dichotic
group (Figures 5-6), combined with distinct hypotheses for each training condition, led
to the decision to perform separate statistical analyses for the binaural and dichotic
groups, respectively.**

2. Test-retest effects – Untrained group

To exclude the possibility that pre-/post-test performance differences were due to test-retest
effects rather than training effects, we conducted analyses to assess the reliability of the
categorical perception tests when tested at two timepoints. Three repeated-measures
ANOVAs were performed with Session (**pre-**, **post-test**) and Pair (/ki-gi/, /ti-di/) as within-
subject factors, examining the untrained group's performance on the magnitude of the

<footnote n="1">¹ two participants across the full sample exhibited performance exceeding 2 SD from the mean; however, removing them did not change the pattern of results, so they were kept in the analysis.</footnote>
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discrimination peaks (d') (Figure 4, top), identification slopes, and boundaries (Figure 4, bottom).

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No significant main effect of Session was observed for any measure, *d'*: *F* < 1; slope: *F*(1, 19) = 1.91, *p* = .182; boundary: *F* < 1. Additionally, no significant Session × Pair interaction was found, *d'*: *F*(1, 19) = 1.54, *p* = .229; slope: *F*(1, 19) = 1.96, *p* = .177; boundary: *F* < 1.

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The results confirm the reliability of the categorical perception tests, validating their use in assessing the impact of the training conditions.

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Discrimination task

/ki-gi/ pairs

<figure><img src="image_4.png" /></figure>

/ti-di/ pairs

<figure><img src="image_5.png" /></figure>

Identification task

<figure><img src="image_6.png" /></figure>

<figure><img src="image_7.png" /></figure>

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Figure 4. Mean sensitivity to differences (discrimination task) for /ki-gi/ and /ti-di/ continua (top), and mean percentages of /k/ and /t/ identification (bottom), at pre- (dotted line) and post-test (solid line) in the untrained group. Error bars represent standard errors.

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3. Binaural training program: pre- versus post-tests
To evaluate the training effect on the binaural group (pre-, post-test), we analyzed the magnitude of discrimination peaks (d') (Figure 5, top), and the identification slopes and boundaries (Figure 5, bottom) separately for the trained /ki-gi/ and untrained /ti-di/ syllables, using two-tailed paired-sample t-tests with Bonferroni corrections.

For the discrimination task, the analysis revealed a significant increase in *d'* following binaural training for the trained pair /ki-gi/, *t*(19) = 2.15, *p* = .045, *d* = 0.49, but not for the untrained pair /ti-di/, *t*(19) = 1.27, *p* = .220, *d* = 0.25. In the identification task, no significant change was observed in the slope for either pair (*t*<sub>s</sub> < 1), but the boundary for the trained pair shifted significantly to the right, *t*(19) = 3.50, *p* = .002, *d* = 0.74, primarily due to an increased perception of /g/ as voiced at VOT+10: *t*(19) = 4.41, *p* < .001, *d* = 0.76. The training factor had no significant impact on the boundary for the untrained pair (*t* < 1).

These results align with previous research providing evidence for the effectiveness of HVPT-based training programs for enhancing perception of trained L2 phonemes; however, progress was restricted to the trained consonants and did not transfer to other phoneme pairs (as also shown in Maye & Gerken, 2001; Olson, 2021; Tamminen et al., 2015).
Discrimination task

/ki-gi/ pairs

<figure><img src="image_8.png" /></figure>

/ti-di/ pairs

<figure><img src="image_9.png" /></figure>

Identification task

<figure><img src="image_10.png" /></figure>

<figure><img src="image_11.png" /></figure>

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Figure 5. Mean performance in the binaural group. Sensitivity to differences in the discrimination task (top) and percentages of identification (bottom) for the trained /ki-gi/ (left) and untrained /ti-di/ (right) syllables for the pre-test (dotted line) and post-test (solid line). Error bars represent standard errors.

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4. Dichotic training program: pre- versus post-tests

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Following the demonstration that the categorical perception tasks did not show test-retest effects, and the observed benefits of the binaural training program for trained pairs, we next assessed whether dichotic stimulation led to improvements in categorical perception for both trained and untrained consonants. Training effects were analyzed in the dichotic group using two-tailed paired-sample *t*-tests (Bonferroni corrected), separately for trained and untrained pairs.
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In the discrimination task, the sensitivity (d') significantly increased after dichotic
training for the trained pair, t(19) = 2.42, p = .026, d = 0.57, and marginally for the untrained
pair, with a moderate effect size, t(19) = 2.06, p = .053, d = 0.47 (Figure 6, top).

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In the identification task, there was no significant change in the slope for either the
trained pair (t < 1) or the untrained pair, t(19) = 1.53, p = .142. However, the boundary shifted
significantly rightward for both the trained pair, t(19) = 3.53, p = .002, d = 0.71, and the
untrained pair, t(19) = 3.29, p = .004, d = 0.75. This shift toward longer positive VOTs for
voiceless stop consonants was more consistent with English phonetic rules, suggesting a
perceptual change. As illustrated in Figure 6, these shifts were particularly driven by
increased perception of /g/ as voiced at VOT0, t(19) = 2.17, p = .043, d = 0.63, and VOT+10
ms, t(19) = 4.03, p < .001, d = 0.79, as well as increased perception of /d/ as voiced at
VOT+20, t(19) = 5.30, p < .001, d = 0.76. These improvements occurred for VOTs of the
English voiceless consonants which were particularly ambiguous for French speakers if they
used French phonetic rules to interpret them.

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<figure><img src="image_12.png" /><figcaption>Figure 6. Mean performance in the dichotic group. Sensitivity to differences in the discrimination task (top) and percentages of identification (bottom) for the trained /ki-gi/ (left) and untrained /ti-di/ (right) syllables for the pre-test (dotted line) and post-test (solid line). Error bars represent standard errors.</figcaption></figure>

Taken together, these results suggest that both binaural and dichotic perceptual training enhance perception of trained English phonetic contrasts. However, dichotic training resulted in a transfer also to untrained material, suggesting generalization of learned rules. These transfer effects were evident in improved identification and discrimination of untrained consonants, with a medium effect size. These results highlight the benefit of perceptual training in general, as well as the additional benefit of dichotic presentation for enhancing perception of untrained material. Therefore, these findings support the AST model (Poeppel, 2003) and the featural approach to L2 learning (de Jong et al., 2009; Olson, 2019), emphasizing the potential of dichotic training for learning and generalizing sub-phonemic rules.
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III.

EXPERIMENT 2: ELECTROPHYSIOLOGICAL EVALUATION OF

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DICHOTIC TRAINING

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Experiment 1 yielded three key insights: 1) categorical perception tests are reliable; 2) binaural training based on HVPT principles improves categorical perception in late learners of L2, but the benefit did not transfer to untrained phonemes; and 3) dichotic training, designed to engage the LH or RH based on VOT durations, improves performance for trained phonemes and leads to transfer of skills to untrained phonemes. Based on these behavioral changes, it is particularly interesting to investigate how dichotic training may influence underlying neural responses.

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While categorical perception tasks assess explicit processing of attended speech, they do not capture pre-attentional mechanisms or neural responses. The mismatch negativity (MMN) component in EEG recordings is automatically elicited by perceptual deviants (Näätänen et al., 1989), and can be used as a measure of pre-attentive perception. The MMN provides a reliable neural index of automatic change detection, independent of attention and task-related effects, such as motor preparation (Kujala et al., 2007; Näätänen et al., 2007). The amplitude of the MMN has been shown to increase when the deviants belong to the listener's phonological system (Sams et al., 1985). Further, the MMN has been shown to differentiate native from non-native contrasts in both children (Shestakova et al., 2003) and adults (Ylinen et al., 2006), making it a reliable tool to measure changes in pre-attentive phonetic processing.

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Experiment 2 employed the passive oddball paradigm, using /ki/ and /gi/ as standard and deviant stimuli (and vice versa), to test whether dichotic training induces a change in the neural response to phonetic features in L2. Following dichotic training, an increase in MMN amplitude was hypothesized, along with changes in brain asymmetry when processing short vs. long VOTs, consistent with the LH and RH involvement predicted by the AST

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model for short- vs. long-duration events. Only the dichotic training group was assessed, as
the hypothesis specifically targeted hemispheric changes associated with this condition.

A. Method

1. Participants

Sixteen participants from the dichotic group in Experiment 1 ($M_{age} = 21.60, SD = 2.90$;
14 females) agreed to participate in Experiment 2.

2. Materials

The experiment presented two blocks of English CV syllables, using /ki/ and /gi/ stimuli
selected from the /ki-gi/ continua in Experiment 1 for their typical VOTs. The voiced
consonant /g/ had a VOT+10 and the voiceless /k/ had a VOT+60.

3. Procedure

Participants underwent EEG recording during a passive listening task (oddball paradigm) at pre- and post-test. Testing occurred individually in a sound-proof room, with participants seated in a comfortable armchair in front of a screen. They selected a movie from a list of visually engaging, muted cartoons without subtitles. Sounds, normalized for intensity, were presented binaurally through Beyerdynamics DT 770 Pro 250# headphones. Participants were instructed to focus on the movie and disregard the sounds, to prevent attention-dependent ERP components that might interfere with the MMN response (Näätänen et al., 2007). Stimuli were administered using Presentation software (v.14.9, www.neurobs.com).

The experiment included 506 items divided into two blocks: one with /gi/ as the standard and the other with /ki/, presented in counterbalanced order across participants. Each block consisted of 85% standards and 15% deviants. Stimuli were pseudo-randomized, with at least four standards preceding each deviant. Standards following deviants were excluded from analyses. Each block lasted for 5 minutes, with a rest period between blocks, resulting in a
total recording time of 10 minutes. This experiment followed the categorical perception tasks conducted at the **pre-** and **post-test** stages.

4. EEG data acquisition and preprocessing

EEG was recorded continuously from 32 scalp sites (Electro-Cap International, INC., according to the international 10–20 system) using the Biosemi ActiveTwo EEG system (Version 5.36, 02-06-2006), with a sampling rate of 512 Hz and a 24-bit resolution. Seven active external electrodes were placed on the face: four around the eyes to monitor ocular movements (vertical and horizontal electro-oculograms), one on the nose, and two on the left and right mastoids. Individual electrode offsets were adjusted to remain stable below ± 20 mV.

Data were analyzed offline with the ERPLAB module (v.1.0.0.42) within the EEGLAB toolbox (v.9.0.2.3.b) for Matlab (v.7.0.9.R2009b). The EEG signal was bandpass filtered between 0.1 and 30 Hz (12 dB/oct). Data were epoched from –200 to 800 ms relative to stimulus onset. Baseline was corrected by subtracting the mean voltage in the 200 ms prestimulus interval from each sample in the epoch. Automatic artifact rejection excluded epochs with a trace exceeding ± 100 µV.

For each condition, signals were averaged per participant and re-referenced to the average of the two mastoid channels. ERPs time-locked to the syllable were averaged offline for each participant at each electrode site across experimental conditions. MMN responses were extracted by subtracting the average standard waveform from the average deviant waveform for each participant in each experimental block.

B. Data analyses

The MMN was identified for each participant as the most negative peak occurring between 100-300 ms post-stimulus onset at electrode Fz (Kujala et al., 2007), and MMN
mean amplitude was calculated. Time windows were selected based on MMN latency over Fz for all participants, separately for each deviant type. For the /ki/ deviant, a 150–250 ms window was used, while for the /gi/ deviant, a 200–300-ms window was used. Visual inspection confirmed that the MMN for each participant peaked within these windows.

Electrodes F3, Fz, and F4 were grouped to represent the Frontal scalp region of interest; FC1 and FC2 for the Frontocentral region; C3, Cz, and C4 for the Central region; CP1 and CP2 for the CentroParietal region; and P3, Pz, P4 for the Parietal region. This electrode grouping is standard in MMN analyses, as it helps to reveal the front-back distribution of brain responses (Kujala, et al., 2007).

## C. Results

# 1. Pre-training results

To assess the presence of significant MMNs prior to training, two-tailed *t*-tests (Bonferroni corrected) compared the mean amplitude within the MMN window for each of the two experimental blocks against a test value of zero.

In the pre-test, *t*-tests revealed that the mean MMN amplitude differed significantly from zero for /ki/, *t*(15) = 3.06, *p* = .008, *d* = 1.08, but not for /gi/, *t*(15) = 1.11, *p* = .285 (Figure 7, upper panel). **This result may be attributed to the long aspiration in /ki/, which is perceived as a more salient nonrelevant acoustic event than the brief silence following the burst in English voiced stop consonants (Flege, 1991).** Thus, the pre-training MMN likely reflects automatic orientation toward basic physical changes (Sams et al., 1985).
<figure><img src="image_13.png" /><figcaption>Figure 7. Grand averages (µV) of the ERPs elicited by the standard (solid line) and deviant (dotted line) stimuli at Fz, presented before (upper panel) and after (lower panel) dichotic training, with /ki/ (left panel) or /gi/ (right panel) as the deviant.</figcaption></figure>

## 2. Dichotic training effects

A repeated-measures ANOVA assessed the impact of dichotic training on the MMN amplitude, with Training (pre, post-test), Voicing (/ki/, /gi/), and Position (Frontal, Frontocentral, Central, Centroparietal, Parietal) as within-participant factors. Significant interactions were investigated using two-tailed paired-sample t-tests (Bonferroni correction). A significance level of $p \le .05$ was used, and effect sizes were evaluated.

The ANOVA showed no significant MMN amplitude difference between frontal and frontocentral electrodes, $t(15) = 1.20, p = .249$. However, MMN amplitude was higher at frontocentral electrodes compared to more posterior sites (Table 1), as indicated by a significant main effect of Position, $F(4, 60) = 6.41, p < .001$, $\eta_p^2 = .30$. This finding replicated the literature and confirmed the presence of an MMN. There was no significant main effect of Training or Voicing (all $p_s > .201$).
The Training × Voicing interaction, $F(1, 15) = 6.23, p = .025, \eta_p^2 = .29$, revealed that the MMN increased after dichotic training for the English /gi/ deviant (pre-training, $M = -0.42, SD = 1.50$; post-training, $M = -1.53, SD = 1.32), t(15) = 2.40, p = .030, d = 0.26$, but no change occurred for the /ki/ deviant. All other interactions were non-significant (all $p > .579$).

<table><caption>Table 1. Results of two-tailed *t*-tests comparing MMN amplitudes between frontocentral electrodes and more posterior sites.</caption><thead><tr><th>Electrodes positions (mean MMN amplitude)</th><th>t test (df = 15)</th><th>p</th><th>Cohen's d</th></tr></thead><tbody><tr><td>Frontocentral (-1.30 μV)</td><td></td><td></td><td></td></tr><tr><td>Central (-1.14 μV)</td><td>-2.68</td><td>.017</td><td>0.03</td></tr><tr><td>Centroparietal (-1.07 μV)</td><td>-2.25</td><td>.040</td><td>0.14</td></tr><tr><td>Parietal (-0.82 μV)</td><td>-4.30</td><td>&lt;.001</td><td>0.32</td></tr></tbody></table>

Additional analyses examined the expected changes in hemispheric asymmetry for VOT duration processing post-training. Following training, the involvement of the LH was hypothesized to increase for /gi/, while the involvement of the RH was anticipated to increase for /ki/.

As shown in Figure 8, during pre-test, MMN amplitude for /ki/ was significantly higher at left than right anterior electrodes in both frontal and frontocentral areas, respectively $t(15) = 2.34, p = .034, d = 0.85$, and frontocentral: $t(15) = 2.52, p = .024, d = 0.78$. This asymmetry disappeared in the post-test: there was no difference between the left and right electrodes in frontal: $t(15) = -0.16, p = .873$; or frontocentral: $t(15) = -0.23, p = .822$ areas.
<figure><img src="image_14.png" /></figure>

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Figure 8. Mean MMN amplitude (μV) for English stimuli before (left panel) and after (right panel) dichotic training, for the left (black) and right electrodes (white). Error bars represent standard errors.

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In summary, following dichotic training, the MMN increased for the English voiced deviant /gi/, indicating that its short positive VOT was processed as a phonetic feature characterizing a phonological category, which was distinct from the category associated with the standard /ki/. This result supports the expected change in the relationship between phonetic features and phonological categories, aligning with the 'two-category assimilation' process (PAM-L2) or a 'similar scenario' (L2LP). Previous research has linked larger MMNs to changes in the perception of abstract features (Tervaniemi et al., 1994) and increased linguistic expertise (Näätänen et al., 2001). The increased MMN for the /gi/ deviant post-training may reflect enhanced English-like pre-attentive categorization, including at the neural level (Kujala et al., 2007; Näätänen et al., 2007).

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Additionally, the post-training decrease in LH involvement for deviants with long VOTs (i.e., /ki/) suggests a change in appropriate cerebral asymmetry for event durations, as
proposed by the AST model (Poeppel, 2003; Poeppel et al., 2008), extending the model to
sub-phonemic features.

## IV. GENERAL DISCUSSION

The current study investigated whether a brief perceptual training program could facilitate the acquisition of the voicing contrast for English consonants among adult French speakers. It was hypothesized that dichotic presentation, stimulating the LH with voiced stop consonants and the RH with voiceless stop consonants, would enhance learning compared to training with binaural presentation. This hypothesis was grounded in the AST model suggesting complementary hemispheric dominance for short and long events. The hypothesis was tested using categorical perception tasks and pre-attentional EEG measures. Results indicated that both binaural and dichotic training improved behavioral categorical perception for trained phonemes, and that this benefit extended to untrained phonemes only with dichotic training, indicating generalization of sub-phonemic rules. Additionally, after dichotic training, an MMN response emerged for English voiced stop consonants, with a change in hemispheric lateralization aligning with the long VOT of these English consonants. These findings support the hypothesis that phonetic perception can be enhanced in late learners with both binaural and dichotic stimulation. Further, dichotic stimulation training can support the processing of untrained phonemes, improving featural-level associations with phonemes, neural sensitivity to the English voicing contrast, and hemispheric specialization for short and long VOTs.

### A. Enhancing English voicing perception using a brief training program

Prior to training, all participant groups exhibited categorical perception of voiced vs. voiceless stop consonants in English, as evidenced by the shape of their identification and discrimination curves, but the categorical boundary was more appropriate to English
579 following perceptual training than at this initial step. This result is consistent with
580 production data demonstrating that adult Spanish-speaking learners of English produce
581 English voiceless stop consonants with intermediate VOT values that are longer than
582 Spanish voiceless stop consonants, but shorter than those produced by native English
583 speakers (Flege, 1991). This result is relevant, as Spanish voiced consonants are
584 associated with short positive VOTs, like in French. Relatedly, in the present study, post-
585 training results indicated a perceptual shift toward more English-like VOT perception.
586 Specifically, an increase in the peak of discrimination suggested improved boundary precision
587 (Medina et al., 2010). Moreover, the identification boundary shifted from VOT+12 to
588 VOT+19, aligning more closely with the phonemic boundary of VOT+20 captured by the
589 discrimination task, signaling that perception was based on sub-phonemic rules more in line
590 with English phonology.

591 Additionally, the VOT boundary shifted from a French-like location (approximately
592 VOT0; Caramazza & Yeni-Komshian, 1974) to a more English-like one (around VOT+30;
593 Lisker et al., 1977). Despite the English voiced [g] containing a positive VOT of 10 or 20
594 ms that is prone, together with the voiceless [kʰ], to ‘single-category assimilation’ to /k/,  
595 it was better identified as /g/ following the two trainings, suggesting a shift toward what  
596 would be considered a ‘two-category assimilation’ process in PAM-L2 (Best & Tyler,  
597 2007) or a ‘similar scenario’ in L2LP (Escudero, 2009; van Leussen & Escudero, 2015).
598 In summary, the training program (with both binaural and dichotic presentation) grounded in  
599 HVPT principles (Grenon et al., 2019; Saito et al., 2022; Strange & Dittman, 1984)  
600 successfully enhanced adult learners’ perception of phonetic features and their phonological  
601 roles for trained English phonemes, without explicit instruction. These results support existing  
602 research suggesting that adult L2 learners can improve their phonological processing of
temporal features (Cebrain & Carlet, 2014; Mennings et al., 2002; Olson, 2019; Tamminen et al., 2015), as predicted by the SLM-r and PAM-L2 models.

## B. Enhancing attentional categorical perception through dichotic stimulation

Dichotic stimulation proved more effective than binaural stimulation in enhancing the phonetic perception of French speakers learning English, resulting in improved perception of both trained and untrained phonemes. This finding suggests that dichotic training, which engages asymmetric hemispheric recruitment for processing short vs. long events, facilitates the formation of new sub-phonemic associations between VOT and phonological voicing values for English stop consonants. The current finding aligns with previous research showing an advantage of this same dichotic training program applied to vowel length difference learning (Bouhon et al., 2023). This previous training was also grounded in the AST model, and successfully improved the perception of the non-native duration differences between English /i/ and /i:/ for French learners, with skill transfer observed from perception to production (Bouhon et al., 2023).

Another tentative explanation for the generalization of dichotic training to untrained contrasts is that it facilitates learning by distributing processing resources adequately across both hemispheres. Alternatively, one might argue that the novel dichotic presentation may have heightened learners’ curiosity and attention, promoting deeper processing of stimuli. To further investigate the role of hemispheric asymmetry in processing phonetic feature durations, as suggested by the AST model, future studies could implement a reversed dichotic condition, with voiceless English stop consonants presented to the right ear and voiced stop consonants to the left. Based on the current findings and hypotheses, performance in this condition would likely be lower than in the two trained groups of the current study. This reversed condition was avoided in the present study to prevent disrupting brain processing and
potentially hindering the appropriate engagement of the LH and RH in processing short and long acoustic events, impacting L2 speech processing.

While improvement after binaural training could reflect learning of individual phonemes in line with segmental models (SLM, PAM), dichotic training may work at the sub-phonemic level, aligning with the featural approach to L2 learning (de Jong et al., 2009). This perspective is neglected in favor of segmental models in educational contexts, but it is supported by the current results, encouraging development of sub-phonemic learning tools.

**Combined, these results support the use of dichotic stimulation for training English perception skills in adult French learners.**

### C. Extension of the AST to phonetic features

The benefits of dichotic training observed in this study align with the predictions of the AST model. As outlined above, the hemispheric asymmetry proposed by this model has not previously been applied to phonetic features. AST links rapid gamma oscillations in the left non-primary auditory cortex with phoneme processing, while slow theta oscillations in the right non-primary auditory cortex are associated with syllable processing (Boemio et al., 2005; Poeppel, 2003). The VOTs analyzed in this study are at the sub-phonemic level, suggesting that the AST model can be extended to encompass phonetic features.

Gamma oscillations, with frequencies above 30.5 Hz, are sufficiently rapid to process VOTs in English voiced stop consonants, which last under 30 ms (Cho & Ladefoged, 1999). In the current study, dichotic training effectiveness in learning a generalizable association between short phonetic features (VOT) and voiced English consonants may be facilitated by the dominance of gamma oscillations in the LH.

Furthermore, dichotic training may enhance the processing of longer VOTs in English voiceless stop consonants by engaging the RH, associated with slower oscillations. The AST model suggests that theta and alpha oscillations in the RH process longer acoustic events,
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such as syllables and prosody within the 4-10 Hz frequency range (Giraud & Poeppel, 2012).

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However, VOTs in English voiceless stop consonants can range from 30-150 ms (Docherty, 1992; Kupske, 2017), potentially corresponding to frequencies in the 10-33 Hz range, overlapping with beta oscillations (13-30 Hz) for VOTs between 30-76 ms and part of the alpha band (10-13 Hz) for VOTs between 76-100 ms. Although evidence for alpha and beta oscillations in the RH related to sound durations are limited, studies have shown that theta and alpha activity is enhanced in the RH when non-verbal sounds are presented to the left ear (Jiwani et al., 2021), suggesting the availability of these oscillations in the RH.

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Beta oscillations have also been observed to dominate in response to 30-500 ms acoustic transients (in the right associative auditory cortex; Giroud et al., 2020). Additionally, higher magnetoencephalographic responses to amplitude modulations at 2 Hz, 4 Hz, but also 10 Hz (alpha) have been noted in the RH compared to the LH in typical-level adult readers, but not in dyslexic adults (Hämäläinen et al., 2012), suggesting that the RH can support long VOT processing. Finally, auditory evoked cortical magnetic field recordings indicate that, in the auditory cortex, the LH processes periodic noise repetition rates within a 25 ms temporal window, while the RH processes them within a 50-200 ms window. This window in the RH may be well-suited to processing most of the VOTs in English voiceless stop consonants (Keceli et al., 2015). **These findings, combined with the current results, collectively support the proposition to extend the AST model to phonetic features, particularly VOTs.**

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D. Enhancing pre-attentional phonological processing in L2 via dichotic training

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The finding that dichotic training enhanced the MMN amplitude in response to the English voiced deviant /gi/ aligns with the behavioral data from Experiment 1, providing evidence for improved perception of short positive VOTs as cues to voiced stop consonants at

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both behavioral and neural levels. Prior to training, the MMN also revealed greater LH involvement as compared to the RH in the processing of the English voiceless stop consonant /k/ by French-speaking English learners, contradicting predictions from the AST. This finding suggests an overreliance on abstract phonological representation in the L1, associating voiceless consonants with LH processing due to short VOTs in French. This cerebral misalignment with long acoustic cues is consistent with MEG findings showing higher LH phase locking to long noises in dyslexic adults (Hämäläinen et al., 2012). The unexpected LH dominance in long VOT processing indicates that French learners of English require support in optimizing brain asymmetry for temporal processing in English (Bouhon et al., 2023). Dichotic training in the current study effectively facilitated this asymmetric hemispheric processing of the English voicing contrast.

However, it should be noted that the current study measured the MMN only in the dichotic training group, and the EEG results should be considered preliminary, as the results cannot yet be directly interpreted as linked to dichotic stimulation. Future research should examine the effects of binaural training on the MMN to compare its effectiveness with that of dichotic training, including comparisons with a passive control group. The comparisons with a control group showing similar baseline performance to the trained groups are also required to confirm the training's benefits. Nevertheless, two neural changes were observed following dichotic training: enhanced preattentional sensitivity to English /gi/ (short VOT) and reduced LH involvement in processing English /ki/ (long VOT). These findings suggest changes at the encoding featural level in L2 learning, consistent with de Jong et al. (2009) and the current behavioral results.

Conclusion
This study provides new evidence supporting the potential for improvements in late L2 learning through brief perceptual training, and advocates for the use of neurologically-inspired methodologies, such as dichotic stimulation, to facilitate this training. The findings suggest that adult French-speaking learners of English can enhance their phonological perception of phonetic features in L2, refine representations of L2 phoneme boundaries, and strengthen appropriate phonetic-phonological associations, thereby increasing pre-attentional sensitivity to L2 features. These results underscore the value of targeted training programs that focus on sub-phonemic contrasts without explicit instructions. However, further investigation of potential long-term effects is necessary. Considering the crucial role of phonetic accuracy in lexical identification, and previous research on vowel perception (Bouhon et al., 2023), these findings encourage further exploration of dichotic stimulation as a tool for enhancing L2 learning.

## V. AUTHOR DECLARATIONS

MB and NB designed the experiment, analyzed results and wrote the original draft. MB, JC, AFo and NB ran the experiments, MB, AFi, BT, and NB reviewed and edited the manuscript. This study was funded by MB doctoral grant supported by Contentsquare – Contentsquare Foundation. The authors have no conflicts to disclose. The experiment was approved by the French Ethics Committee (Comité de Protection des Personnes, n°21-AMBU-01) and participants gave informed consent after the procedures had been explained to them. The data that support the findings of this study are available from the corresponding author upon reasonable request.

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