3.1.1 Materials

The audio recordings of Tasks 6_01 and 6_02 in the J-AESOP corpus (see Section 2.2) were examined. The speech samples were annotated in Praat TextGrid format ( Boersma & Weenink, 2024), first by automatic forced alignment tools (HTK ( Young et al., 2006) for Task 6_01 and Julius ( Lee & Kawahara, 2019) for Task 6_02) and then manually modified by trained phoneticians in the J-AESOP team. Annotators also marked segment-level phonological events such as vowel devoicing (e.g., /kitakaze/ ‘North Wind’ ➔ [ki̥takaze]) and lengthening (e.g., /taijou/ ‘Sun’ ➔ [taijoː]) in Japanese, as well as word-level speech events such as substitution (e.g., misreading cloak as coat ), repetition (e.g., Then the Sun … Then the Sun shone out warmly), and insertion (e.g., wrapped around in a warm cloak) by assigning ‘tags’ to the relevant words (underlined above).

3.1.2 Data retrieval and acoustic measurement

Based on the annotations, a total of 34963 Japanese vowels (/i/ = 6504, /e/ = 3598, /a/ = 15713, /o/ = 6504, /u/ = 2444) produced by the 154 L1 Japanese speakers were retrieved for acoustic analysis. Their production of 10775 English monophthongal vowels (/i/ = 1591, /ɪ/ = 3196, /ɛ/ = 911, /æ/ = 1451, /ʌ/ = 1094, /ɑ/ = 1095, /u/ = 893, /ʊ/ = 544) was also retrieved. Devoiced and lengthened vowels, as well as vowels in tagged words, were excluded.

For each vowel interval, the mean F1 and F2 frequencies were measured using Praat. The built-in Burg algorithm was used for formant estimation, with the formant ceiling setting at 5000 Hz for male speakers and 5500 Hz for female speakers. The obtained F1 and F2 values were then Z-transformed per speaker ( Lobanov, 1971), which effectively eliminates spectral variations caused by physiological differences while preserving phonological and cross-linguistic contrasts ( Adank et al., 2004). The normalization was performed across Tasks 6_01 and 6_02 so that the formants could be directly compared across L1 Japanese and L2 English speech.

We begin our analysis by examining the potential acoustic correlates of perceived L1 foreign accent. Given the finding in Section 2 that L1 foreign accented was typical of L2 speakers with overseas experience, here we focus on the 55 speakers with LOR > 0. We first hypothesized that the formant values of L1 vowels in foreign-accented speech are dislocated from those of non- or less-accented speech, presumably due to the assimilation or dissimilation of L1 vowels to acquired L2 vowels. To test this, we used the following LME model: lmer ( L 1 . accentedness ∼ vowel : F 1 . norm + vowel : F 2 . norm + ( 1 | JP . rater ) , df . subset ) (3) where the dependent variable of L1 accentedness score was predicted by the interaction between vowel type (/i, e, a, o, u/) and normalized formant values (F1 and F2), with random intercepts for native Japanese raters. The results are shown in Table 6, where all fixed effects turn out to be statistically significant. For example, the significant negative estimates for the interactions between the vowel /i/ and the two types of formant values indicate that lower F1 and F2 (i.e., raised and more back articulation) predict a higher L1 accentedness score.

To complement the above results, we also show in Figure 4 the production of L2 English vowels by the same 55 speakers as a function of their L2 nativelikeness scores (cf. Yazawa et al. (2023a)). Each circle shows the mean Z-normalized formant values of a 0.50 score range (i.e., 1.25-1.75, 1.75-2.25, etc., as in the bins of Figure 1), with darker shades representing higher scores. The arrows point from lowest through intermediate to highest score ranges based on these means, ignoring apparent outliers. The mean formant values of L1 Japanese vowels are also shown alongside as gray boxes (averaged across the L2 score ranges because the by-range differences in F1 and F2 values were too subtle to plot). Since speakers with higher L2 nativelikeness scores were perceived as having a stronger L1 foreign accent for the current sample, a comparison of Table 6 and Figure 4 can be useful to examine how acquired L2 vowels might affect L1 vowel production.

The comparison shows that only some of the results can be straightforwardly explained by L1-L2 segmental assimilation or dissimilation. For example, the results for L1 /e/ in Table 6, where lower F1 and higher F2 values predict a higher L1 accentedness score, can be interpreted as a case of dissimilation from the adjacent L2 vowel /ɛ/, which shows the opposite pattern as a function of L2 nativelikeness score in Figure 4. That is, as speakers become more proficient in the L2 (and thus more accented in the L1), their L1 /e/ production is raised and fronted while that of L2 /ɛ/ is lowered and backed, resulting in an increased distance between the two categories. In contrast, the results for L1 /o/ in Table 6, where higher F1 and lower F2 values predict a higher L1 accentedness score, can be interpreted as a case of assimilation to L2 /ɑ/, which shows the same pattern according to L2 nativelikeness scores in Figure 4. That is, as speakers become more proficient in the L2 (and thus more accented in the L1), the L1 and L2 vowels move to the same direction (similar to what Turner (2023) called “tandem drift”). The results for the other three L1 vowels, however, were more mixed. As for /i/, while the negative estimate for F1 (i.e., raising) in Table 6 may be attributed to its assimilation to L2 tense /i/ (see Figure 4), the negative estimate for F2 (i.e., backing) would contrarily indicate dissimilation from this very L2 category. The same goes for L1 /u/, where the negative F1 estimate (i.e., raising) would indicate assimilation to L2 /u/ or /ʊ/, whereas the negative F2 estimate (i.e., backing) would indicate dissimilation from these two categories. L1 /a/ is a similar case, where the positive F1 estimate (i.e., lowering) would indicate dissimilation from L2 /æ/ or /ʌ/, while the positive F2 estimate (i.e., fronting) would indicate assimilation to these categories. The supposed assimilation-dissimilation patterns are, therefore, inconsistent at best.

Another explanation becomes possible when we shift our focus from individual L1-L2 category contrasts to the whole vowel space. Considering the suggested phonetic changes in Table 6—raising and backing of /i/, raising and fronting of /e/, lowering and fronting of /a/, lowering and backing of /o/, and raising and backing of /u/—one can envision a clockwise chain shift. Judging from Figure 4, such movements of L1 vowels seem to be helpful for maintaining their distance from the developing L2 categories.

We now move on to examine the potential acoustic correlates of perceived L1 comprehensibility. Here we investigate all 154 speakers, since more proficient L2 speakers were found to be more comprehensible in their L1 regardless of overseas experience in Section 2. The first acoustic parameter to be investigated is the ‘compactness’ of vowel categories in the F1-F2 acoustic space. Kartushina and Frauenfelder (2014) found that individuals with more compact L1 vowel categories tend to show more accurate L2 vowel production, presumably because the existing L1 categories overlap less with the target L2 vowels. SLM-r ( Flege & Bohn, 2021) provides a theoretical explanation of this finding through its “category precision” hypothesis, which posits that individuals with relatively precise L1 categories are better able to discern phonetic differences between an L2 sound and the closest L1 sound, thereby increasing the likelihood of new L2 category formation. If this is also true for the current sample, we can hypothesize that higher L1 comprehensibility in more proficient L2 learners is also due to their more compact or precise production of L1 vowel categories.

Following Kartushina and Frauenfelder (2014), we first calculated the compactness score (CS) per speaker and vowel type, using the following formula: CS = σ F 1 norm σ F 1 norm π (4) where σ F 1 norm and σ F 2 norm are the standard deviations of Z-normalized F1 and F2 values. The score thus reflects the area of the normalized vowel ellipse per speaker and vowel type. While Kartushina and Frauenfelder (2014) used raw formant values because they had only female speakers, we used Z-normalized values because our data contain both male and female speakers. Note that, somewhat counterintuitively, a larger CS represents a larger vowel ellipse and therefore a less compact category.

The calculated five CSs were then added to obtain the global compactness score (CS _G) per speaker: CS G = ∑ i = 1 n CS i (5) where a larger CS _G would indicate generally less compact vowel categories. This is illustrated in Figure 5, which shows the vowel ellipses of two male speakers with relatively large and small CS _G values (6.71 for JM003 and 1.87 for JM026), respectively. It can be seen that the ellipses, which reflect one standard deviation of normalized F1 and F2 values, are less compact and more overlapping for the former speaker than for the latter.

Another acoustic parameter we will investigate here is formant dispersion, since compact vowel categories can still overlap with one another if they are not sufficiently dispersed and non-compact vowel categories can still be clearly distinguishable from each other if they are sufficiently dispersed. Thus, we can derive an alternative hypothesis that higher L1 comprehensibility in more proficient L2 learners is due to their more dispersed L1 vowel production.

While there are several metrics for measuring formant dispersion, we used the vowel formant dispersion (VFD) metric of Karlsson and van Doorn (2012). To calculate the VFD, we first need to define the center of the F1-F2 vowel space for each speaker. The coordinate of the midpoint along the vertical (F1) axis is calculated according to: F 1 m = 1 n ∑ i = 1 n F 1 i (6) for all vowels, and thus the midpoint is simply the mean of all F1 values. On the other hand, the position of the center along the horizontal (F2) axis is defined as a weighted midpoint: F 2 wm = 1 n ∑ i = 1 n F 2 i { V ( F 2 , F 1 ) : F 1 < F 1 m } (7) and is therefore based only on vowels whose F ₁ value is lower than the F ₁ midpoint (i.e., more raised than the average vowel height). According to Karlsson and van Doorn (2012), this strategy makes the weighted center robust to missing productions of a suitable low front vowel, as in Japanese. Once the center of the F ₁- F ₂ vowel space is established, each vowel is converted into a vector starting from that point. Each vowel vector is defined to have a length according to: VFD i = ( F 1 i − F 1 m ) 2 + ( F 2 i − F 2 wm ) 2 (8) where the vector length, called VFD, is expected to increase for expanded vowel spaces and decrease for spaces with reduced articulation. This is illustrated in Figure 6, which shows vowel vectors of two female speakers with relatively small and large mean VFD values (268.98 for JF012 and 493.02 for JF051), respectively. Note that the values are in Hz because the effect of dispersion would be eliminated if they were Z-normalized.

Now that the acoustic parameters are defined, the question is whether individual differences in vowel compactness or dispersion predict the degree of perceived L1 comprehensibility. To test this, we used the following LME model: lmer ( L 1 . comprehensibility ∼ global . CS + mean . VFD + ( 1 | JP . rater ) , df . all ) (9) where the fixed effects of CS _G and mean VFD, both of which are specific to each speaker, predicted their L1 comprehensibility score, with random intercepts for native Japanese raters. Although mean VFD tended to be larger for female speakers (because the metric is based on raw formant values), speakers’ gender was not included because it did not improve the model fit according to likelihood ratio tests. The result of the model is shown in Table 7. While both fixed effects were statistically significant, the positive estimate for CS _G contradicts our first hypothesis because a larger CS _G (i.e., less compact articulation) is associated with a higher L1 comprehensibility score. In contrast, the positive estimate for mean VFD suggests that more dispersed articulation predicts a higher L1 comprehensibility score, which is consistent with our second hypothesis.

To fully support the second hypothesis, however, we must also demonstrate that individuals with more dispersed L1 vowel production are more proficient in the L2. To test this, we fitted the following CLMM: clmm ( L 2 . nativelikeness ∼ global . CS + mean . VFD + ( 1 | EN . rater ) , df . all ) (10) where the fixed effects of CS _G and mean VFD predicted the L2 nativelikeness score, with random intercepts for native American English raters. While only mean VFD would be relevant to the hypothesis testing, CS _G was also included in the model to test whether the result of Kartushina and Frauenfelder (2014) can be replicated with the current data. The result of the model is shown in Table 8, where neither effect reached statistical significance. The non-significant effect of CS _G is perhaps best illustrated in Figure 5, as the nativelikeness scores for the two speakers happen to be nearly equal (4.17 for JM003 and 4.25 for JM026). Therefore, our prediction that individuals with less overlapping L1 categories (due to compactness, dispersion, or both) would achieve a higher level of L2 proficiency based on the “category precision” hypothesis of SLM-r ( Flege & Bohn, 2021) was not supported. To sum up this section, higher comprehensibility in L1 speech is associated with more dispersed vowel articulation, but the degree of L1 vowel dispersion does not adequately predict L2 proficiency.

The primary purpose of the current study was to investigate the potential effects of L2 learning on perceived accentedness and comprehensibility of L1 speech. To this end, we examined 154 L1 Japanese learners of L2 English in the J-AESOP corpus with varied L2 learning experience and proficiency levels. The rating results revealed that more proficient L2 speakers tended to be perceived as more foreign-accented in the L1, but only if they had lived in an English-speaking country; no such relationship was found for those who had never lived abroad. Subsequent acoustic analyses of vowel production suggested that the degree of perceived foreign accent could not be straightforwardly attributed to either assimilation or dissimilation of individual L1 and L2 categories but rather to a system-wide phonetic change. In contrast, more proficient L2 speakers were consistently perceived as more comprehensible in the L1, regardless of the presence or absence of prior overseas experience. Acoustic analyses suggested that the degree of perceived comprehensibility was associated with the dispersion, rather than compactness, of vowel production, although neither dispersion nor compactness in L1 vowel production predicted L2 proficiency levels.

4.2.1 Accentedness

The rating results for accentedness suggest that L2 learners do not necessarily gain an L1 foreign accent as they become proficient in the L2. Rather, strong L1 accentedness seems to be associated with the experience of living in an L2-speaking (or non-L1-speaking) environment for an extended period of time. Therefore, to answer our first research question, a perceptible L1 foreign accent is likely due to L1 disuse rather than L2 interference. It may thus be misleading to refer to this phenomenon as “backward transfer” because the acquired L2 system is not directly affecting the existing L1 system; the term “attrition” would be more appropriate in this sense. It should be noted, however, that the degree of perceived L1 foreign accent for the current sample was less profound than that of the migrant populations in the previous studies ( de Leeuw et al., 2010; Kornder, 2022). This may be because our speakers maintained their L1 oral skills through everyday conversations with their parents and siblings while abroad and/or partially reversed L1 attrition after re-immersion into the L1-speaking environment back in Japan. While the LOR information in the corpus does not reflect these possibilities, the effects of relative L1 exposure while abroad and the length of L1 re-immersion in Japanese-English bilingual returnees is extensively discussed in Laméris et al. (2024).

Our acoustic analysis of vowel production also indicated an intriguing pattern of potential L1 phonetic change in proficient L2 speakers with overseas experience: clockwise chain shift in the F1-F2 space. While no previous study has reported such a pattern, our finding would not contradict previous reports of system-wide phonetic change due to drift or attrition ( Guion, 2003; Mayr et al., 2012; Turner, 2023). Thus, to answer our second research question, perceived L1 accent seems to reflect a system-wide change in all sound categories, rather than individual assimilation or dissimilation of adjacent categories between the two languages. Caution is warranted, however, because the previous studies observed a systematic lowering or raising of all vowel categories, whereas in the current study the direction of change varied from vowel to vowel (similar to Kornder (2022)). Nevertheless, the motivation for these diverging patterns may be the same, i.e., to maintain a perceptual distinction between the L1 and L2 sounds, as proposed by Guion (2003).

4.2.2 Comprehensibility

A novel finding of this study was that a higher level of L2 proficiency consistently predicted a higher level of L1 comprehensibility (consistent with our previous pilot study ( Yazawa et al., 2023b)). This was somewhat surprising given the negative correlation between L1 accentedness and comprehensibility (cf. Figure 2), but perhaps not entirely unexpected since a strong foreign accent does not necessarily reduce perceived comprehensibility for L2 speech ( Munro & Derwing, 1995). Thus, to answer our final research question, the influence of L2 learning on perceived L1 comprehensibility can be positive. Logically speaking, there are two possible explanations for the current finding: (i) learners whose L1 speech is comprehensible tend to acquire a high level of L2 proficiency, and (ii) as learners become more proficient in the L2, their L1 speech becomes more comprehensible. The first possibility was theoretically predicted by the “category precision” hypothesis of SLM-r ( Flege & Bohn, 2021), as outlined in Section 3.3. However, the acoustic analyses did not support this prediction, since neither compactness nor dispersion of L1 vowel articulation was related to L2 nativelikeness scores (in contrast to Kartushina and Frauenfelder (2014) who found a link between L1 vowel compactness and L2 proficiency). It is then worth noting that the VFD metric did predict the perceived degree of L1 comprehensibility, because if this viable acoustic predictor of L1 comprehensibility does not predict L2 proficiency, then (i) is not very feasible. The alternative possibility is (ii), which, although no current model of L2 speech acquisition offers an explicit explanation for it, seems plausible in nature. If L2 learning involves an effort to clearly articulate speech sounds to make oneself better understood, then learners may extend this skill to their L1 production, thus increasing its comprehensibility (even though the resulting speech may differ from monolingual norms). If such an effect turns out to be true, then this L2-related ‘amelioration’ or ‘enrichment’ of L1 speech would be an important advantage of bilingualism, especially in the current era where comprehensibility is considered more important than nativelikeness.

In this study, we conducted a large-scale cross-sectional investigation of L1 phonetic change in native Japanese speakers with various L2 English learning experience and proficiency levels using the J-AESOP corpus. The overall results seem to suggest two main conclusions. First, perceived L1 foreign accent likely results from L1 disuse rather than L2 interference, where a learner’s L1 pronunciation is shifted from monolingual norms at a system-wide rather than category-specific level. Second, L2 learning can have a positive influence on perceived L1 comprehensibility, rather than individuals whose L1 speech is more comprehensible being better equipped for L2 learning. However, the current investigation is limited in that the corpus data do not inform us of how the learners’ pronunciation has actually changed over time; we are, after all, comparing different speakers from different linguistic backgrounds. What seems necessary to confirm and extend the current research, then, is a longitudinal study of intra-speaker acoustic-phonetic change and its communicative impact, similar to previous studies (e.g., Kornder (2022)) but with a larger number of speakers. To this end, a longitudinal bilingual speech corpus, which is far less common than cross-sectional ones such as J-AESOP, is expected to be useful. While building such a corpus would be labor-intensive and time-consuming, we believe that the benefits outweigh the effort. A preliminary project towards this goal has been initiated, and we look forward to sharing what it brings about in the future.