Intensive Foreign Language Learning Reveals Effects on Categorical Perception of Sibilant Voicing After Only 3 Weeks

Time Course of Perceptual Adaptation

Two of the most central speech learning models, the perceptual assimilation model (PAM and PAM-L2; Best, 1995; Best & Tyler, 2007) and the speech learning model (SLM; Flege, 1995), both posit that perceptual adaptation to foreign speech sound categories occurs early in the process of acquiring a foreign language (Best & Tyler, 2007; Flege, 1995). Best and Tyler (2007) argue for their cutoff at 6 to 12 months of exposure by pointing to, on the one hand, Aoyama, Flege, Guion, Akahane-Yamada, and Yamada (2004) who found perceptual learning during 6 to 18 months rather than within the first 6 months of exposure; and on the other hand, the primacy of phonology as a building block and stepping stone for vocabulary and grammatical learning as a conceptual motivation for their perceptual adaptation window within 6 to 12 months of experience with the foreign language.

Flege et al. (1997) investigated effects of experience extending beyond the 6 to 12 months of exposure. They found more native-like perception of English vowels as an effect of prolonged LOR in the United States for four groups of nonnative English learners (native German, Spanish, Mandarin, and Korean speakers). The inexperienced groups’ mean LOR was 0.7 years, and the experienced groups’ mean LOR was 7.3 years. There are, however, several studies that do not show effects of prolonged experience with the foreign language on the learners’ speech perception and production (for reviews, see Best & Tyler, 2007; Moyer, 1999). In response to this, Flege and Liu (2001) conducted a study comparing two groups of Chinese students and two groups of Chinese nonstudents living in the United States on their perception of word-final English stops. This comparison revealed a beneficial effect of LOR on the perception of word-final English stops only between the two groups of students, not between the two groups of nonstudents, suggesting that the amount and quality of the exposure to the foreign language are crucial factors for perceptual adaptation.

Adaptation to foreign speech sounds has also been investigated in more experimental settings using targeted laboratory training paradigms varying in their degree of complexity of the tasks and stimuli used. Bradlow, Akahane-Yamada, Pisoni, and Tohkura (1999), Lively et al. (1994), and Logan et al. (1991) used relatively specific phonetic identification and discriminations tasks in combination with both speaker variability and non-synthesized (i.e., natural) stimuli for training Japanese learners on the English contrast between /r-l/. Chandrasekaran et al. (2010), Perrachione et al. (2011), and Wong and Perrachione (2007) used sound-to-meaning paradigms for teaching native English listeners to discriminate foreign lexical pitch contrasts (i.e., Mandarin pitch contours superimposed on English pseudowords). Common to both segmental contrast learning (Bradlow et al., 1999; Lively et al., 1994; Logan et al., 1991) and lexical pitch contrast learning (Chandrasekaran et al., 2010; Perrachione et al., 2011; Wang et al., 1999; Wong & Perrachione, 2007) was that the targeted laboratory training paradigms showed perceptual adaptation within just 1 to 4 weeks. Furthermore, the learning effects of these training regimes can be retained up to 3 and 6 months after training without sustained training (Bradlow et al., 1999; Lively et al., 1994; Wang et al., 1999).

To investigate the temporal discrepancy between the SLMs’ proposed window of 6 to 12 months of exposure for perceptual adaptation and the adaptation results from laboratory training paradigms within just 10 to 30 days, we tested the language officer cadets four times during their education: immediately before their language training started (T0), after 3 weeks (T1), after 6 months (T2), and after 19 months (T3). T0 was intended to reflect baseline with no or very minimal knowledge of the target language. T1 was intended to test the very early and rapid perceptual adaptation similar to the laboratory training paradigms. T2 was intended to test Best and Tyler’s (2007) early adaptation window of 6 to 12 months of experience. T3 was intended to examine the even later stages in the foreign language learning, nearly parallel to the later time intervals in Flege et al.’s (Flege et al., 1997; Flege & Liu, 2001) studies showing some effect of prolonged linguistic immersion.

To our knowledge, perceptual adaptation to the Arabic and Dari sound contrasts used in the present study has not been investigated in the context of foreign language sound learning thus far.

Foreign Speech Sound Contrasts

The target languages for the two groups of participants were Arabic (Modern Standard Arabic [MSA] and Egyptian Arabic) for one group (n = 8) and Dari (Afghan Farsi) for the other (n = 12). For the choice of stimuli in the present study, we were, therefore, constrained by the Arabic phonology and the Dari phonology.

We identified a phonemic sound contrast in each target language that was not phonemic in the other, or in Danish (the cadets’ mother tongue). This allowed us to treat the two groups as each other’s control group, which was a crucial feature of the experimental design since it would have been very difficult to find a suitable “active” control group. The Arabic stimuli consisted of the contrast between the glottal and pharyngeal fricatives (/h-ħ/), and the Dari stimuli consisted of the contrast between the voiced and voiceless sibilants (/ʒ-∫/; Figure 1).

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Figure 1.

Spectrograms and amplitudes of both Arabic and Dari stimuli. (a) Arabic stimuli showing the four steps from the full 11-step continuum: (1) [hæ] + 0 ms of frication (“ha00”); (2) [hæ] + 28 ms of frication (“ha28”); (3) [hæ] + 49 ms of frication (“ha49”); and (4) [hæ] + 70 ms of frication (roughly equivalent to [ħæ], “ha70”). And (b) Dari stimuli also showing the four steps from the full 11-step continuum: (1) original [∫a] (“sha01”); (2) [∫/ʒa], more [∫] than [ʒ] (“sha04”); (3) [∫/ʒa], more [ʒ] than [∫] (“sha07”); and (4) original [ʒa] (“sha11”). Both sets of four sounds were used in the behavioral discrimination task. See Table 1 and the description of the stimuli in the text for fuller descriptions of the continua and the production of the stimuli.

We tested the cadets’ perceptual adaptation using two related experiments: an identification task (2AFC) and a discrimination task (same-different, i.e., AX). A steeper slope of the identification (ID) function indicates more consistent identification of stimuli into either of two (phonological) categories. Such categorical perception can be further substantiated by higher discrimination for stimulus pairs straddling the category boundary indicated by the ID function compared with pairs within either category.

On the basis of the models of speech learning and the research on laboratory auditory training, we hypothesized:

Identification: (a) that the slopes of the participants’ ID functions to the sound categories of their target language, but not their nontarget language, would become steeper as learning progressed. (b) That the steepening of the ID slopes would be detectable within the first 3 weeks of learning.

Participants

Participants consisted of two groups of volunteer cadets from the Institute for Languages at the Royal Danish Defence College, enrolled in their first year of the language officer education at the onset of the study. One group was studying Dari (Afghan Farsi) and consisted of 12 participants (seven women, five men); the other group was studying Arabic (learning both MSA and Egyptian Arabic [Masri]) and consisted of nine participants of which one dropped out of the education and hence also the study after 4 weeks (n = 8; three women, five men). A total of 22 language officer cadets were enrolled in their first year when the study started. Of these 22, one dropped out (as already stated), and one (Arabic learner) did not participate in the study, otherwise all those enrolled participated. The two groups served as each other’s control groups since the stimuli were constructed in such a way that the Dari stimulus contrast was not phonemic in Arabic, and the Arabic stimulus contrast was not phonemic in Dari (see the Stimuli section below).

The participants had been prescreened by the Royal Danish Defence College on the basis of their school achievements, study skills, intelligence, and emotional stability among a large group of applicants (∼200) prior to enrollment into the 2-year program. All participants were native Danish listeners, and all had been hearing tested in relation to admission to the Royal Danish Defence College, on the basis of which they all reported having near-normal to normal hearing. None reported any history of neurological or psychiatric illness.

Throughout the 19 months, all 20 participants underwent comprehensive and intensive language training at the Institute for Languages at the Royal Danish Defence College. Intensive language learning in this respect entails language learning as a full-time job. The teaching was conducted both by native speakers and language experts of the relevant languages, and the curriculum involved many varied activities including extensive conversational practice with native speakers. The first 6 months focused almost exclusively on language learning, after which also teaching in cultural aspects and military strategy was included. After 3 weeks (T1), the cadets were familiar with the new sounds of their target language, and they had begun learning the writing system and acquiring vocabulary. After 6 months (T2), the cadets were proficient enough to conduct short conversations in their target language, and at the end of their education (T3) they were capable of functioning as interpreters and cultural experts in the field. We treated these levels of foreign language proficiency as basic (T1), intermediate (T2), and advanced (T3).

A few of the participants had some minor knowledge of either Arabic (n = 5) or Dari (n = 2) prior to enrollment (mainly in the form of 1- to 3-month-long stays abroad or evening classes during a semester; one Dari learner reported that his father was Iranian and spoke Farsi, but he clearly stated that he was not bilingual in relation to Farsi; and one Arabic learner had studied Arabic at the university for 3 years). At the initial measurement at T0, there were no significant differences between the group of learners with some prior knowledge of Arabic and the rest of the learners on either the slopes of their ID functions or the peaks of their discrimination functions in relation to the Arabic stimuli. Nor were there any significant differences between the two learners with some prior knowledge of Dari/Farsi and the rest of the learners at T0 on the same dependent variables in relation to the Dari stimuli (see the Results section for details on the statistics).

The two groups did not differ significantly on age (Dari, M = 24.2 [SD = 2.6]; Arabic, M = 23.4 [SD = 2.6]; t(18) = 0.64, p = .53), years of education (Dari, M = 16.7 [SD = 2.1]; Arabic, M = 16.0 [SD = 2.5]; t(18) = 0.67, p = .51), or number of foreign languages spoken (Dari, M = 3.6 [SD = 1.0]; Arabic, M = 4.1 [SD = 2.0]; t(18) = −0.80, p = .44). On the basis of Wallentin’s (2009) critical review of the putative gender differences in relation to language, we did not include gender as a matching criterion for the two groups.

Stimuli

The stimuli varied in two contrasts, one which was phonemic in Dari and one which was phonemic in Arabic. The language officer cadets were expected to be excellent language learners (since they were prescreened on, among several other things, their language learning abilities). We, therefore, opted for contrasts that had been reported to be difficult for L2 learners to acquire.

The Dari contrast consisted of the sibilant voicing contrast between /∫/ and /ʒ/ (Entezar, 2010). For this choice, we relied on a combination of personal communication with the coordinating Dari teacher at the Institute for Languages (I. G. Smilianov, personal communication, July 23, 2012), and the phonologies of Danish (Basbøll, 2005; Grønnum, 2005), Dari (Entezar, 2010), and Arabic (Watson, 2007). The teacher reported that in his experience the cadets generally faced the most difficulties in acquiring the voicing contrast for the Dari sibilants (I. G. Smilianov, personal communication, July 23, 2012). Danish has a phonemic contrast between /s-ɕ/, but it has no voiced sibilants (Grønnum, 2005, 2009). [ʒ] exists as an allophone of the phoneme /ʤ/ in the Levantine dialects of Arabic (Watson, 2007), but the group of Arabic learners in the present study were learning MSA and Egyptian Arabic, in which the corresponding phoneme is realized as [ʤ] and [g], respectively (Watson, 2007). Hence the contrast’s lack of phonemic status for the Arabic learners was still upheld. We, therefore, opted for the /∫-ʒ/ contrast with the expectation that this would be the most difficult contrast in the Dari phonology for the Dari-learning cadets to successfully adapt to.

The Arabic contrast consisted of the contrast between /h/ and /ħ/ where /ħ/ is mainly realized with pharyngeal constriction and retracted tongue root (Bin-Muqbil, 2006; Laufer & Baer, 1988; Watson, 2007). The constriction of the lower pharynx results in a prolonged and strengthened frication for the pharyngeal fricative [ħ] compared with the glottal fricative [h] (Obrecht, 1968), as well as a lowering of the adjacent high vowels (/i/ and /u/), but only minimally for the low vowel /a/ used in the present study (Bin-Muqbil, 2006; Watson, 2007). For the choice of Arabic stimuli in the present study, we relied on a combination of a report by Burnham (2013) stating that the /h-ħ/ contrast is one of the most difficult, if not the most difficult contrast for learners of Arabic to acquire, and the phonologies of Danish (Basbøll, 2005; Grønnum, 2005), Dari (Entezar, 2010), and Arabic (Watson, 2007). Danish has a glottal fricative /h/, but no pharyngeal fricatives. The Dari alphabet includes the letters corresponding to both the Arabic pharyngeal fricative /ħ/ () and the Arabic glottal fricative /h/ (), but neither of these are realized in spoken Dari (Entezar, 2010). On this basis, we opted for the pharyngeal-glottal fricative contrast with the expectation that this would be one of the most challenging contrasts for the Arabic-learning cadets.

Relevant Dari syllables ([∫a:] and [ʒa:]) were recorded from a male native Dari speaker using an SM58 Vocal Microphone (Shure Inc., Niles, IL, USA) in a sound-attenuated room. Relevant Arabic syllables ([hæl] and [ħæl]) were taken from recordings of a male native Arabic speaker. ¹ The Dari stimuli were then constructed by cross-splicing the recorded syllables so that the same vowel [a] with a duration of 109 ms was used for both Dari stimulus categories, resulting in [∫a] and [ʒa], both with a total duration of 299 ms, hence the duration of the sibilance was 190 ms (both voiceless and voiced). The same procedure was applied to the vowel in the Arabic stimuli so that the same vowel [æ] with a duration of 90 ms was used for both Arabic stimulus categories. The [h] was manipulated to resemble [ħ] by inserting 70 ms of frication from the [ħ]-recording into the [h] from 35 ms and onwards (see below for more details), resulting in [hæ] with a total duration of 178 ms and [hæ] + 70 ms with a total duration of 248 ms (roughly equivalent to [ħæ]). Since the participants were native Danish listeners and vowel length is phonemic in Danish (Basbøll, 2005, pp. 79–82; Grønnum, 2005, pp. 100–101), the duration of [æ] was not adjusted to compensate for the durational difference between [h] and [ħ].

Stimulus continua, each with 11 even-spaced steps, were created for both the Dari stimuli and the Arabic stimuli. For the Dari voicing contrast, we used the procedure described by Stevenson (1979) and Repp (1981) to mix the two sounds ([∫a] and [ʒa]) using 11 even-spaced levels of attenuation so that the first step from [∫a] to [ʒa] consisted of a mix between a completely unattenuated [∫a] and a completely attenuated [ʒa], thus rendering the original [∫a]. The next step from [∫a] to [ʒa] consisted of a mix between [∫a] attenuated by 0.92 dB and [ʒa] attenuated by 20.00 dB, corresponding to a 9/10- and a 1/10-power ratio of the two original sounds, respectively. This balance was step-wise reversed until the final step from [∫a] to [ʒa] consisted of a mix between a completely attenuated [∫a] and a completely unattenuated [ʒa], thus resulting in the original [ʒa] (see Table 1). This procedure for stimulus continuum generation has also been used by Broersma (2005, 2008, 2010) for voiceless-voiced fricative contrasts such as [s-z] and [f-v], acoustically very similar to the [∫-ʒ] used in the in present experiment. Also McQueen (1991), Norris, Mcqueen, and Cutler (2003), and Dufour, Kriegel, Alleesaib, and Nguyen (2014) have used the procedure for creating continua for voiceless fricative contrasts such as [f-s] and [s-∫].

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Table 1.

Gain Table for the Dari Stimuli, [∫a] and [ʒa].

	[∫a]										[ʒa]
Stimuli	sha01	sha02	sha03	sha04	sha05	sha06	sha07	sha08	sha09	sha10	sha11
[∫a] LW ratio	0	−1/10	−2/10	−3/10	−4/10	−5/10	−6/10	−7/10	−8/10	−9/10	−1
[ʒa] LW ratio	−1	−9/10	−8/10	−7/10	−6/10	−5/10	−4/10	−3/10	−2/10	−1/10	0
[∫a] dB gain	0.00	−0.92	−1.94	−3.10	−4.44	−6.02	−7.96	−10.46	−13.98	−20.00	−Inf
[ʒa] dB gain	−Inf	−20.00	−13.98	−10.46	−7.96	−6.02	−4.44	−3.10	−1.94	−0.92	0.00

For the Arabic contrast, 70 ms of pharyngeal frication was taken from 24 to 94 ms into a realization of /ħæ/ and cut into 10 equally long bits of 7 ms. These cutouts were then one-by-one inserted into the frication of the glottal [hæ] from 35 ms into the sound and onwards, matching amplitude profiles of the frication and cutouts in order to avoid audible clippings in the sounds. This cross-splicing procedure resulted in an 11-step continuum ranging from [hæ] to a close approximation of [ħæ].

The stimuli were validated by one native Arabic listener and three native Dari listeners in a pilot study. They were presented with the same two experimental tasks as described below for the language learners. Instead of the arbitrary category labels of 1 and 2, they were presented with the written symbols corresponding to the relevant syllables in their native language (i.e., and for Arabic and and for Dari). The results of this pilot study are presented in gray dashed lines in Figures 2, 3, 5 and 6. The native Arabic listener showed a category boundary close to “ha42” which is evident from the gray vertical dashed lines in Figure 2(b-i, iii) and the peak in hit rates in Figure 6(a) and (c). The native Dari listeners showed an average category boundary close to “sha05” which is visualized by the gray vertical lines in Figure 2(b-ii, iv) and by the peak in d′ scores in Figure 3(b) and (d), as well as the peak in hit rates in Figure 6(b) and (d). The combination of steep ID functions and discrimination peaks straddling the category boundaries that both the native Arabic and Dari listeners showed for their respective stimuli validated the stimuli as representative exemplars from the phonologies of Arabic and Dari.

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Figure 2.

Participants’ identification functions to both sets of language stimuli across time. (a) Averages of the fitted slope values of participants’ identification functions to the Arabic stimuli (i) and Dari stimuli (ii) across the four times of measurement. Error bars show the standard error of the mean (SEM) with across participant differences removed (see Cousineau, 2005; Morey, 2008 for more details) in order to best reflect the tests that the significance asterisks refer to, namely the single-factor repeated measures ANOVAs. (b) Averaged observed values and identification functions interpolated from the averages of the participants’ slope and intercept values for each time of measurement and for each set of language stimuli. Darker colors denote later times of measurement. The vertical dashed lines mark the learners’ average category boundaries between the two stimulus categories. Data from one native Arabic listener for the Arabic stimuli (a, i) and (b, i–iii) and the averaged data from three native Dari listeners for the Dari stimuli (a, ii) and (b, ii–iv) are shown in gray as a reference for the learners’ responses. Asterisks denote significant effects of Time (p < .05).

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Figure 3.

Mean discrimination data (d′) for the two groups across the four times of measurement and for each set of language stimuli. Darker colors denote later times of measurement. Asterisks denote significant main effects of Stimulus pair (p < .05). Data from one native Arabic listener for the Arabic stimuli (a) and (c) and the averaged data from three native Dari listeners for the Dari stimuli (b) and (d) are shown in gray as a reference for the learners’ responses. Error bars denote the standard error of the mean (SEM, no error bars are shown for the native listeners).

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Figure 5.

Individual identification slope values at all four times of measurement (T0–T3) for the Dari stimuli. The dashed gray lines represent the average of three native Dari listeners.

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Figure 6.

Mean hit rates for the two groups across times of measurement and for each set of language stimuli. Darker colors denote later times of measurement. Data from one native Arabic listener for the Arabic stimuli (a) and (c) and averaged data from three native Dari listeners for the Dari stimuli (b) and (d) are shown in gray as a reference for the learners’ responses. Error bars denote the standard error of the mean (SEM, no error bars are shown for the native listeners).

For the discrimination task, we selected two sounds from each of the stimulus continua together with the two endpoints (these were the same sounds that were used in the EEG experiment; Nielsen et al., in prep). For the Dari stimuli, these were thus “sha01”, “sha04”, “sha07”, “sha11”. The slightly asymmetric distribution was to ensure that the largest acoustic difference between either of the sound pairs did not straddle the category boundary identified by the native Dari listeners (i.e., “sha04-sha07” did not contain the largest acoustic difference). Otherwise, we could not have distinguished a potential effect of better discrimination across the category boundary from a potentially confounding effect of a larger acoustic difference. For the Arabic stimuli, the four selected sounds were “ha00”, “ha28”, “ha49”, “ha70”. Again, we ensured that the asymmetry in acoustic difference did not center on the category boundary identified by the native Arabic listener (i.e., “ha28-ha49” did not contain the largest acoustic difference).

Task and Procedure

All participants were tested with two behavioral experiments: an identification task and a discrimination task. Each task had a Dari condition and an Arabic condition. The order of the two conditions within the tasks was counter-balanced across participants. We used Etymotic ER•2 insert earphones to deliver the auditory stimuli binaurally at a hearing level of approximately 80 dB. The execution and control of the stimuli presentation was carried out by Presentation software (Neurobehavioral Systems, Inc., Albany, CA, USA).

Data Analysis

All data analyses of the behavioral data were conducted using MATLAB (R2010a, The MathWorks Inc., Natick, MA) and IBM SPSS Statistics version 20 for Mac OS X.

Identification

There was a significant main effect of Language on the steepness of the slopes of the learners’ ID functions, F(1, 18) = 40.0, p < .001, with their slopes to the Dari stimuli being steeper than their slopes to the Arabic stimuli, suggesting that across the board both groups of learners more consistently partitioned the Dari stimulus continuum into two categories than they did with the Arabic stimulus continuum. There was also a significant main effect of Time on the learners’ slope values, F(3, 54) = 6.1, p = .001. Post hoc pairwise comparisons revealed that the learner’s slopes were overall steeper at T2 than at T0, F(1, 18) = 7.3, r = .54, p = .014, as well as at T3 compared with T0, F(1, 18) = 17.1, r = .70, p = .001. This means that on average across both groups and the two sets of stimuli, the learners’ showed steeper slopes after 6 and 19 months of learning, that is, improved categorical perception. However, the learning effects expressed in such a broad main effect of Time are difficult to disentangle from mere adaptation to the experimental paradigms. There was no significant main effect of Group, F(1, 18) = 1.3, r = .26, p = .27. There were no significant interaction effects. Keeping our initial hypotheses in mind, we explicitly note that the three-way Group × Language × Time interaction was thus not significant, F(2.5, 44.2) = 1.1, r = .16, p = .34. However, such complex three-way interaction terms are vulnerable to large individual differences within a limited number of participants as in the present study. We had, therefore, planned for four repeated measures ANOVAs to test for any learning effects within each group to either set of stimuli. These are presented in the following section.

Discrimination

There was a significant main effect of Language on the learner’s d′ scores, F(1, 18) = 31.4, p < .001, with their overall d′ scores to the Dari stimuli being larger than those to the Arabic stimuli. There was also a significant main effect of Stimulus pair on the learners d′ scores, F(2, 36) = 12.5, p < .001. Post hoc pairwise comparisons revealed that the learners’ d′ scores were on average higher for the first pair (i.e., either “ha00-ha28” or “sha01-sha04”) than for the third pair (“ha49-ha70” or “sha07-sha11”), F(1, 18) = 9.6, r = .59, p = .006, as well as higher for the second pair (“ha28-ha49” or “sha04-sha07”) than for the third pair (“ha49-ha70” or “sha07-sha11”), F(1, 18) = 34.3, r = .81, p < .001. There was no significant main effect of Group, F(1, 18) < 1, r = .09, p = .71.

There was a significant interaction effect of Language × Stimulus pair, F(1.7, 30.7) = 27.1, p < .001. This indicates that the location of the peaks of the learners’ d′ scores differed between the two sets of stimuli. To explore this interaction effect, we conducted post hoc pairwise comparisons of each of the three combinations of stimulus pairs in one set of the stimuli to their corresponding combination of pairs in the other set of stimuli. These revealed two significant interactions: The learners’ d′ scores were higher for the second Dari pair (“sha04-sha07”) than for the first Dari pair (“sha01-sha04”) while their d′ scores were higher for the first Arabic pair (“ha00-ha28”) than for the second Arabic pair (“ha28-ha49”), F(1, 18) = 56.7, r = .87, p < .001. And the average difference between their d′ scores to the second and third pairs was larger for the Dari pairs than for the Arabic pairs, F(1, 18) = 33.4, r = .81, p < .001, however, both groups still showed higher d′ scores for the second than the third pair. There was also a marginally significant interaction between the first and third pairs between the two sets of stimuli, F(1, 18) = 4.3, r = .44, p = .053, trending toward a larger difference between d′ scores for the two pairs for the Arabic stimuli than for the Dari stimuli. These interaction effects suggest that the location of the learners’ discrimination peaks differed between the two sets of language stimuli. We examine the locations of these discrimination peaks in more detail in the following section.

There were no other significant interaction effects. And in relation to our initial hypotheses, we note that the four-way Group × Language × Time × Stimulus pair interaction was thus not significant, F(5.0, 90.1) = 1.4, r = .12, p = .227. Again, four-way interaction terms require a substantial number of participants in order to show significant effects if these effects are small as in the present study. We had therefore, as mentioned in the previous section, Statistical tests, planned for four repeated measures ANOVAs with Time and Stimulus pair as within-subject factors in order to test for any learning effects on the d′ scores within each group and each set of stimuli. These are presented in the following section.

Correlations Between Grades and Rates of Change

After both 17 weeks and 40 weeks of language training, the cadets were evaluated by an internal exam at the Institute for Languages. They were evaluated on four tasks: listening, speaking, reading, and writing. Since we investigated foreign language sound learning, we focused on the grades from the listening and the speaking task. The grades were given on the Danish grading scale ranging from −3 to 12, ² which we treated as an ordinal scale, rather than an interval scale, due to its somewhat peculiar distribution of grades (−3, 00, 02, 4, 7, 10, 12, where 02 is the lowest grade needed to pass an exam).

To investigate potential correlations between the cadets’ sound learning effects and their more general learning outcomes, we conducted Spearman’s rank correlations on the two groups’ changes in slope to the Dari stimuli between T0 and T1, between T0 and T2, and between T0 and T3 with their grades for the listening and the speaking task. To limit the number of correlations that we investigated to a sensible number, we focused exclusively on the measures of sound learning where we had observed significant learning effects, hence only the changes in slope to the Dari stimuli. We thus conducted four correlations for each dependent measure (i.e., we correlated each measure of slope change per group to two exam tasks after both 17 and 40 weeks), and we therefore used Bonferroni-adjusted alpha levels of .0125 per test. These 24 correlations in total revealed one significant correlation. The Dari learners’ changes in slope to the Dari stimuli from T0 to T2 were positively correlated with their speaking grades after both 17 weeks: (r_S(10) = 0.71, p = .01; Figure 4(b)). For comparison, the Arabic learners’ changes in slope to the Dari stimuli for the same time interval (T0 to T2) are also plotted against their speaking grades; there was no significant correlation between the two measures (Figure 4(a)). We observed no other significant correlations for either of the two groups, or time intervals or grades (not depicted).

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Figure 4.

Correlations between changes in slope for the Dari stimuli from T0 to T2 and grades on a speaking task after 17 weeks (approx. at T2). (a) Arabic learners’ changes in the slopes of their identification functions for the Dari stimuli from T0 to T2 did not correlate with their exam grades on a speaking task after 17 weeks. (c) Dari learners’ changes in the slopes of their identification functions for the Dari stimuli from T0 to T2 correlated positively with their exam grades on a speaking task after 17 weeks. The asterisk denotes Bonferroni-adjusted alpha levels of p < .0125.

No Differences due to Prior Experience

At the initial measurement at T0, the group of learners (n = 5) with some prior knowledge of Arabic did not differ significantly from the rest of the learners on the slopes of their ID functions to the Arabic phonemic contrast (with prior experience, M = 0.60, SD = 0.27; without prior experience, M = 0.42, SD = 0.27; t(6.8) = 1.30, p = .24), or on the peak differences of their discrimination functions to the Arabic contrast (with prior experience, M = 0.89, SD = 0.68; without prior experience, M = 0.66, SD = 0.46; t(5.3) = 0.69, p = .52). Nor did the two learners with some prior knowledge of Dari/Farsi differ significantly from the rest of the learners at T0 on the slopes of their ID functions to the Dari phonemic contrast (with prior experience, M = 0.50, SD = 0.59; without prior experience, M = 0.87, SD = 0.51; t(1,2) = −0.85, p = .54), or on the peak differences of their discrimination functions to the Dari contrast (with prior experience, M = 1.39, SD = 0.26; without prior experience, M = 0.90, SD = 0.50; t(1.9) = 2.21, p = .16).

Individual Differences

We only observed statistically significant learning effects for the group of Dari learners. However, visually inspecting Figure 2(a, ii) it seems that the Dari learners’ initial performances were somewhat lower (as well as at T1 and T3) than those of the Arabic learners. None of these differences between the two groups were statistically significant. One possible explanation for these numerical differences comes from inspecting the individual learning progressions of the two groups of learners (Figure 5). The numerical differences between the two group averages thus seem to be mainly due to effects of comparing two groups with large individual differences.

In Figure 5(a), arab3 and arab5 were clearly driving the Arabic learners’ higher slope values at T0. But their high initial performances were not sustained across the following three measurements. At T1, arab2 and arab5 showed native-like performances. And at T3, arab2 and arab3 (and to some extent arab6) excelled. As already mentioned above, arab3 and arab5 had perhaps already at T0 perceptually successfully adapted to the foreign Dari contrast due to their L2 experience with English and French and thus contributed with very steep slopes to the Arabic learners’ group average at T0. However, if this were so, we would expect arab3 and arab5 to consistently show native-like performances across the subsequent measurements, which they did not. Instead, the Arabic learners’ performances changed in both directions over time, and it is difficult to identify a consistent pattern in their performances. And crucially in this context, the group of Arabic learners did not show any statistically significant learning effects on the Dari stimuli over the course of 19 months of learning Arabic, whereas the Dari learners did, in fact, show a consistent increase in slope steepness to the Dari stimuli as an effect of learning (this applies to 11 of the 12 Dari learners, Figure 5(b)).

In Figure 5(b), we see that there were, in fact, a few individuals who showed native-like performances at the later recording sessions (dari7 and dari1 at T2, and dari4 and dari7 at T3). But crucially, the Dari learners’ changes in slope over time seem to show a more consistent pattern than those of the Arabic learners: From T0 to T1, all except for 1 of the 12 Dari learners showed some increase in their slope values (i.e., all except dari9). Hence, the Dari learners showed large differences in the degree to which they improved their slope values (but the majority of them showed improvements), as well as in the offsets of their initial performances. The lack of further statistically significant learning effects (especially between T1 and T2) may therefore be due to these individual differences, as well as differences in the time courses of their improvements (some plateaued earlier than others).

The large individual differences, which we see in Figure 5, are also reflected in the relatively large error bars in Figure 2(a, ii). Note that the error bars have been adapted to best reflect the repeated measures ANOVAs, and hence the differences that they express relate to the progression between times of measurement for the two groups of learners (see Cousineau, 2005; Morey, 2008 for more details). Individual differences in learning foreign language speech contrasts have been attested in several studies (Chandrasekaran et al., 2010; Golestani & Zatorre, 2009; Perrachione et al., 2011; Wong & Perrachione, 2007) showing clear patterns of successful and less successful (sound) learners. The present study, however, was not designed to investigate individual differences within the two groups.

Nonetheless, we obtained the grades from the cadets’ exams after 17 weeks and after 40 weeks. And the Dari learners’ grades on a speaking task showed a significant positive correlation with their changes in identification slope from T0 to T2 (i.e., over the first 6 months), larger changes correlating with higher grades (Figure 4). This suggests that some of the individual differences reflected in the relatively large error bars in Figure 2(a, ii) do reflect meaningful variation in the Dari learners’ degree of perceptual adaptation, as well as the pace at which they adapt. We observe these individual differences despite the fact that the two groups of language officer cadets form a highly select population of skilled language learners. Finally, the correlation between their changes in slope and their speaking grades, but not their listening grades, may be suggestive of a strong link between perception (adaptation) and production, as has also been shown in the laboratory auditory learning settings (Bradlow et al., 1997, 1999; Wang, Jongman, & Sereno, 2003).

Native Listeners of Arabic and Dari

As already mentioned in the Results section, we urge caution in interpreting the responses from the native listeners of Arabic (n = 1) and Dari (mean of n = 3) shown in gray in Figures 2, 3 and 6 due to the small number of informants. Nonetheless, the native listeners seem to show higher slope values for their native contrasts than the two group averages of the Arabic and Dari learners. At the same time, we observe a noteworthy similarity between the native listeners’ and the learners d′ scores in the discrimination task. Such response patterns suggest ceiling effects on this task, which is likely to be the case for the Dari stimuli where the stimulus intervals seem to have been too large to properly detect the learning effects which we observed in the identification task. Hence, the intervals were perhaps also too large to properly discern the performances of skilled L2 learners and native listeners. Interestingly, in the participants’ raw hit rates (see Figure 6), the differences between the native listeners and the learners show up more clearly. Whether this discrepancy in the patterns of the d′ scores and the raw hit rates between the native listeners and the learners could be due to response biases in the small native listener samples cannot be determined on the basis of the present data. But the raw hit rates do suggest differences in the performances of the native listeners and the learners on the discrimination task.

Differences Between the Stimuli

We are somewhat surprised to see that the group of Arabic learners consistently showed stronger categorical perception for the Dari contrast than for the Arabic contrast. But as already stated in the Introduction, Burnham (2013) reported that the Arabic contrast between the glottal and pharyngeal fricatives is a very difficult contrast for learners of Arabic to acquire. We are furthermore surprised not to see any adaptation to this contrast during the course of 19 months of intensive Arabic teaching. The coarticulation cues in the neighboring /i/ and /u/ vowels around /ħ/ (Bin-Muqbil, 2006) lead us to speculate that the Arabic learners relied more on these secondary cues than on the prolonged and strengthened pharyngeal frication within the fricative itself. And since Danish vowels include relatively subtle vowel contrasts (Basbøll, 2005; Grønnum, 2005), it may be that the Arabic learners to some extent could have drawn on their L1 phonology for the general identification of /ħ/ via cues in the neighboring vowels. This speculation remains to be investigated in further depth using more varied stimuli. And finally, following Flege et al.’s (1997; Flege & Liu, 2001) findings of continued perceptual adaptation after several years of linguistic immersion, it may be that these cadets would indeed show some perceptual adaptation to such subtle contrasts after full linguistic immersion during stationing in Arabic-speaking regions.

Implications for SLMs

In the present study, we showed perceptual adaptation to a Dari sound contrast during intensive multifaceted language learning within a time frame similar to those reported by targeted laboratory training regimes (Bradlow et al., 1999; Chandrasekaran et al., 2010; Lively et al., 1994; Logan et al., 1991; Perrachione et al., 2011; Wang et al., 2003; Wong & Perrachione, 2007), that is, within 3 weeks. This is much earlier than the early and rapid perceptual adaptation suggested by Flege’s SLM (1995) and Best and Tyler’s PAM-L2 (Best & Tyler, 2007), which Best and Tyler tentatively place within 6 to 12 months of exposure. Hence, when motivation to learn and amount and quality of input are high, it seems that the time frame for perceptual adaptation during second language learning may indeed mirror that of targeted laboratory training paradigms.

We did not see a similar effect of early and rapid perceptual adaptation with the Arabic learners on the Arabic contrast. In fact, we did not observe any perceptual adaptation at any time interval with the group of Arabic learners. However, for the reasons stated above regarding secondary perceptual cues, we speculate that this was not due to an overall lack of perceptual adaptation, but mainly due to the primary acoustic cue of strengthened and lengthened pharyngeal frication not being sufficiently salient to them given the rich vowel inventory in their native language (Danish). Hence, their lack of perceptual adaptation on the Arabic contrast does not necessarily contradict the SLMs’ predictions of early and rapid adaptation. However, it would be interesting to test the cadets’ categorical perception of the Arabic contrast after prolonged linguistic immersion during stationing in Arabic-speaking regions. Perhaps some foreign contrasts are so difficult to acquire that they require very extensive exposure, even for skilled and motivated L2 learners.

We did, however, also observe considerable individual variation in when the strongest adaptation took place for the Dari learners; (see Figure 5(b)). Half of the Dari learners (n = 6) showed the greatest steepening of their slope from T0 to T1, one fourth (n = 3) between T1 and T2, and the last fourth (n = 3) between T2 and T3. Hence, even though we mainly show evidence in support of a rapid and early window for perceptual adaptation in foreign language learning in the present study, we also show that within a rather homogenous group of skilled language learners, half of them show greatest perceptual adaptation after the initial 3 weeks. We find it plausible to argue that the significant initial adaptation we observe at the group level reflects a general rapid perceptual adaptation to the target language, even earlier than that suggested by Best and Tyler (2007). Further improvements at the later time intervals (nonsignificant at the group level) seem to be more prone to individual variation, which could be a tentative explanation for the lack of consistency in results from cross-sectional immersion studies reported by Moyer (1999).