The Emergence of a Phoneme-Sized Unit in L2 Speech Production: Evidence from Japanese–English Bilinguals

Nakayama, Mariko; Kinoshita, Sachiko; Verdonschot, Rinus G.

doi:10.3389/fpsyg.2016.00175

ORIGINAL RESEARCH article

Front. Psychol., 23 February 2016

Sec. Psychology of Language

Volume 7 - 2016 | https://doi.org/10.3389/fpsyg.2016.00175

This article is part of the Research Topic Bridging Reading Aloud and Speech Production View all 13 articles

The Emergence of a Phoneme-Sized Unit in L2 Speech Production: Evidence from Japanese–English Bilinguals

$\r\nMariko Nakayama$ Mariko Nakayama¹

Sachiko Kinoshita^2,3

Rinus G. Verdonschot^4*

¹Faculty of Letters, Arts and Sciences, Waseda University, Tokyo, Japan
²ARC Centre of Excellence in Cognition and its Disorders, Sydney, NSW, Australia
³Department of Psychology, Macquarie University, Sydney, NSW, Australia
⁴Waseda Institute for Advanced Study, Tokyo, Japan

Recent research has revealed that the way phonology is constructed during word production differs across languages. Dutch and English native speakers are suggested to incrementally insert phonemes into a metrical frame, whereas Mandarin Chinese speakers use syllables and Japanese speakers use a unit called the mora (often a CV cluster such as “ka” or “ki”). The present study is concerned with the question how bilinguals construct phonology in their L2 when the phonological unit size differs from the unit in their L1. Japanese–English bilinguals of varying proficiency read aloud English words preceded by masked primes that overlapped in just the onset (e.g., bark-BENCH) or the onset plus vowel corresponding to the mora-sized unit (e.g., bell-BENCH). Low-proficient Japanese–English bilinguals showed CV priming but did not show onset priming, indicating that they use their L1 phonological unit when reading L2 English words. In contrast, high-proficient Japanese–English bilinguals showed significant onset priming. The size of the onset priming effect was correlated with the length of time spent in English-speaking countries, which suggests that extensive exposure to L2 phonology may play a key role in the emergence of a language-specific phonological unit in L2 word production.

Introduction

Speaking a word naturally requires assembling its phonology. According to the influential language production model by Levelt et al. (1999), this takes place through a process called prosodification. This entails first accessing a word’s phonological segments (e.g., phonemes in English/Dutch), which are then incrementally inserted into a metrical frame (a structure specifying the number of syllables and the stress position). That is, producing a word such as “table” in English will first require access to its phonemes (i.e., /t/ /e/ /I/ /b/ /ə/ /l/) and metrical structure (i.e., bi-syllabic with stress on first syllable) which are then merged together to form the phonological word (i.e., /ter’-bəl/). Constructing phonology on-line is essential for languages such as English and Dutch (on which the Levelt et al. (1999) model is mainly based) as these languages often need re-syllabification depending on the local context. For instance, the sentence “He’ll escort us.” is normally pronounced as /hil-ə-skɔr–təs/. As the cliticized form (/ə-skɔr-təs/) would not be stored in the lexicon, whether the syllable /-skɔr’/ or /-skɔrt’/ will be created depends on the utterance context (Levelt et al., 1999, p. 23). The evidence that this process initially occurs in phoneme-sized units comes from results obtained in Dutch using the implicit priming (also called the form preparation) paradigm (Meyer, 1990, 1991). In this paradigm, participants learn prompt-response pairs (e.g., say “DANS” [dance] when presented with the prompt “feest" [party]). The prompted words are grouped in such a way that they either all overlapped in their initial segment(s) or not. Response words were produced significantly faster when there was overlap (e.g., DANS [dance], DOP [cap], DEUGD [virtue]) compared to when there was no overlap (e.g., DANS [dance], HEKS [witch], STOEP [sidewalk]). This significant facilitation is referred to as the preparation effect. In contrast, rime related overlap (e.g., BOEK [book], DOEK [canvas], SNOEK [pike]) did not produce facilitation, attesting to the incremental left-to-right (i.e., beginning to end) nature of the segment-to-frame association process.

Research on reading aloud has also revealed a similar left-to-right incremental segment-to-frame association process. Masked priming research using English (e.g., Forster and Davis, 1991; Kinoshita, 2000) and Dutch (e.g., Schiller, 2004) has also shown that when a prime is briefly presented (e.g., 50 ms) before a to-be-read-aloud target, naming latencies are significantly faster when the onset phoneme is shared (e.g., pole-PEAR) than when it is not (e.g., take-PEAR). Similar to findings observed with the implicit priming paradigm, no facilitation was observed in masked priming when only the last segments were shared (e.g., Kinoshita, 2000; Schiller, 2008). While the masked onset priming effect was originally interpreted in terms of a serial letter-to-phoneme mapping process (e.g., Forster and Davis, 1991), the emerging consensus is that this left-to-right incremental nature of reading reflects a speech production process (see e.g., Grainger and Ferrand, 1996; Roelofs, 2004; Malouf and Kinoshita, 2007).

The evidence for the left-to-right phoneme-to-frame association process mentioned above has come from European languages, mainly Dutch and English. However, languages differ in many respects, and recently it has been suggested that the unit used to fill the metrical frame may not always be the phoneme, but other languages may employ different unit sizes (see O’Seaghdha, 2015; Roelofs, 2015). For instance, in Mandarin Chinese (hereafter “Chinese”), Chen et al. (2002) and O’Seaghdha et al. (2010) employing the implicit priming paradigm, found reliable preparation effects only when a group of response words overlapped in the first (atonal) syllable; no facilitation was observed when a group of response words overlapped in the onset phoneme. The initial unit involved to build phonology (termed the “proximate unit” by O’Seaghdha et al., 2010) in Chinese, therefore, seems to be the syllable, and not the phoneme (see also You et al., 2012, for related results).

The Proximate Unit of Japanese Word Production

Japanese is known to have a mora-based timing (Warner and Arai, 2001; Kureta et al., 2006). The Japanese mora is a supra phonemic unit that usually involves a CV or V (e.g., /ka/ or /a/), nasal coda (/N/), or a geminate (/Q/) combination, but never a single consonant (e.g., /k/). The mora as a proximate unit has accounted for many Japanese psycholinguistic findings ranging from speech segmentation (e.g., Cutler and Otake, 1994), speech errors (e.g., Kubozono, 1989), and children’s word games (e.g., “shiritori,” in which the players take turns in generating a word that starts with the final mora of the word the other player has produced: e.g., “kobuta” (piglet) – “tanuki”(badger)” – “kitsune” (fox) – “neko” (cat) and so on, see e.g., Katada, 1990). Phonological awareness tests typically assess skills of mora level manipulation, not phonemes (e.g., Sasanuma et al., 1996). The central importance of the mora as the phonological unit in Japanese is further evidenced in the phenomenon of “vowel epenthesis,” a form of phonological restoration: When presented with a non-word containing an illegal consonant cluster like “ebzo,” Japanese listeners hear an illusory vowel, reporting they heard “ebuzo” (Dupoux et al., 2001). Moreover, Japanese listeners show no mismatch negativity in evoked potentials to a change from “ebzo” to “ebuzo,” whereas French listeners do (Dehaene-Lambertz et al., 2000). Additionally, when producing English words, Japanese people typically insert vowels when a word contains phoneme clusters (Broselow and Park, 1995; Broselow and Kang, 2013).

Previous studies on word production also indicate the critical role of the mora during Japanese phonological encoding. Kureta et al. (2006) using the implicit priming paradigm found significant preparation effects in Japanese only when a group of response words overlapped in the initial mora, but not when they merely overlapped in the onset phoneme. Using a masked priming read-aloud paradigm, Verdonschot et al. (2011) reported that Japanese words were read aloud significantly faster when a target was preceded by a prime overlapping in the initial mora (e.g., teki-TENSHI) relative to unrelated primes (e.g., heki-TENSHI). Critically, reading of the Japanese words never benefited from a prime overlapping in the onset phoneme (e.g., tomi-TENSHI) relative to a control prime (e.g., gomi-TENSHI).

One important point in interpreting the masked onset priming effect is the role of script. Indo-European languages like English and Dutch use the alphabetic writing system, in which a letter (or letter cluster e.g., “sh”) maps onto a phoneme. Chinese is written using a logography in which a character maps onto a (morpho-) syllable. Japanese is written both in “kanji” (literally “Chinese characters”), the logography borrowed from the Chinese, and in “kana” (hiragana/katakana), two inventories, consisting of 48 characters each, mapping onto a mora (e.g., www.frontiersin.org [ni] • [ho] • [N] and [ni] • [ho] • [N], for katakana and hiragana, respectively).¹ In the masked priming read-aloud experiments mentioned earlier, all words were presented in their native script, i.e., alphabetic letters in English (e.g., Kinoshita, 2000) and Dutch (e.g., Schiller, 2004) and kana in Japanese (Verdonschot et al., 2011). As noted earlier, an alternative interpretation of the masked onset priming effect in reading-aloud is that it might originate in the mapping of letters to phonemes (Forster and Davis, 1991). From this perspective, the absence of masked onset priming effect in studies that used non-alphabetic script like kana may be interpreted as reflecting the size of the unit involved in the mapping of written script to phonology, rather than the size of the phonological unit involved in speech production. To test this possibility, Verdonschot et al. (2011) conducted two experiments in which Japanese target words were presented in “romaji” (alphabetic transcriptions). However, no significant onset priming effect was found in either experiment, suggesting that for the Japanese speakers, the effect depended on the size of the phonological unit used in speech production rather than print-to-speech conversion.

Phonological Units in L2 Word Production

Given the increasing evidence concerning the difference between languages in the proximate unit (the primary unit used in the phonological encoding process), the logical next step is to investigate how bilinguals process words, and how L2 proficiency modulates this process. Not surprisingly, the earlier L2 is acquired, the more native-like the bilingual speakers’ pronunciation of L2 becomes (see Piske et al., 2001, for a review). As noted by Alario et al. (2010) however, most of research on this issue has focused on the acoustic properties of bilinguals’ speech, and studies focusing on the cognitive mechanisms involved in the spoken production of L2 are very scarce. In particular, it is currently unknown what phonological unit is used in L2 production when bilinguals’ two languages have different unit sizes.

To our knowledge, only one study to date has investigated this matter (Verdonschot et al., 2013). That study involved highly proficient Chinese-English bilinguals to read aloud English targets primed by English words. Naming latency was significantly faster when a target was primed by an onset-related English word (e.g., bark – BENCH) than by an unrelated prime (e.g., dark-BENCH). As noted earlier, the phonological unit of monolingual Chinese speakers is known to be a syllable (e.g., CVC). Therefore, the significant onset priming observed for Chinese-English bilinguals suggests that highly proficient bilinguals used a phonological unit suited to produce L2 words (i.e., phonemes), one that is different in size from the phonological unit normally used in their L1 production (i.e., syllable).

A possible limitation concerning Verdonschot et al. (2013) is that the Chinese-English bilinguals were all highly proficient. It is therefore unknown whether the ability to prepare phonology in the unit of L2 develops with proficiency in L2. Also, Verdonschot et al. (2013) did not include a group of native English speakers. Therefore, it would be important to show that the high-proficient bilinguals behave more like native English speakers than the low-proficient bilinguals in producing a significant onset priming effect with the same set of stimuli.

Present Study

The present study investigated the proximate unit used by Japanese–English bilinguals of varying proficiency in reading aloud L2 (English) words. Specifically, we were interested in whether the L1 Japanese speaker constructs L2 English phonology by placing moras (CVs) or phonemes (specifically consonants, given that a vowel is also a mora) in the metrical frame, and whether the size of the phonological unit is modulated by L2 proficiency. To assess this, low-proficient bilinguals, high-proficient bilinguals and native English monolingual speakers (Experiments 1–3, respectively) read aloud English target words that were preceded either by English prime words that shared the initial onset phoneme (bark-BENCH) or by words that shared the initial CV (i.e., mora; bell-BENCH), with priming effects measured against their respective unrelated primes (dark-BENCH and cell-BENCH). Assuming that the low-proficient Japanese–English bilinguals would use the phonological unit of their first language (the mora), they should show CV (mora) priming effects (bell-BENCH < cell-BENCH), but not onset priming (phoneme) effects (bark-BENCH = dark-BENCH). Alternatively, if a significant onset effect is observed for low-proficient bilinguals, this would then suggest that the proximate unit of L2 English (phoneme) can be adopted relatively early in the course of L2 acquisition. In contrast, high-proficient bilinguals are more likely to show onset effects, based on the finding by Verdonschot et al. (2013) with high-proficiency Chinese–English bilinguals. If so, this would extrapolate previous findings (L1-Chinese vs. L2-English) to a group of bilinguals whose two proximate units also diverge in their two languages (L1-Japanese vs. L2-English). Finally, we expect the group of native English speakers to show significant onset priming effects, in line with previous studies (Forster and Davis, 1991; Kinoshita, 2000; Schiller, 2004).

Experiment 1: Low-Proficient Japanese–English Bilinguals

Methods

Participants

Forty-five low proficient Japanese–English bilingual students from Waseda University (Tokyo, Japan) participated in the experiment in return for payment of 1000 Yen (∼US$8). Their mean TOEIC (Test of English for International Communication) score was 715 (range = 600–790).² This study was carried out in accordance with the recommendations of ‘the Ethics Guidelines for Scientific Research with Human Subjects, Ethics Review Committee on Research of Waseda University’ and ‘the Human Research Ethics Committee of Macquarie University.’ Prior to the experiments, all subjects gave written informed consent in accordance with the Declaration of Helsinki.

Stimuli

The critical stimuli were 42 English medium frequency words (M = 50.3 occurrences per million, Kućera and Francis, 1967). The mean letter length and syllable size of the targets were 5.1 (SD = 0.9) and 1.5 syllables. The syllable length was equally distributed between one (n = 21) or two syllables (n = 21). For each target, four types of monosyllabic English word primes were selected: (1) C prime: a word that had the same onset phoneme with the target (e.g., bark-BENCH), (2) C-control prime: a word that shared all the letters with the onset prime except for the initial letter (e.g., dark-BENCH), (3) CV prime: a word that had the same CV with the target (e.g., bell-BENCH) and (4) CV-control prime: a word that shared all the letters with the CV prime except for the initial letter (e.g., cell-BENCH).³ This ensured that CV prime-target pairs do not have an additional letter (and phoneme) overlap compared with C prime-target pairs (e.g., Verdonschot et al., 2011, 2013). In addition, the bodies of C/CV primes and their controls always had the same pronunciation (e.g., -ark in “bark – dark” or –ell in “bell – cell”). The mean word frequencies (per million) of the four types of primes (C, C-control, CV, CV-control) were comparable: 52.8, 59.4, 58.2, and 50.9, respectively. The word lengths (in letters) of the four types of primes were also comparable (3.6, 3.6, 3.8, and 3.8). For the C and CV conditions, there were two counterbalanced lists; within each condition, half of the targets were primed by the critical primes in one list, and the same targets were primed by their control primes in the other lists, and vice versa. The list of prime and target stimuli used can be found in the Supplementary Materials.

To check the possibility that an absence of masked priming might be due to the lack of familiarity with the alphabetic letters, an identity priming condition was included (and also in subsequent two experiments). The masked identity priming effect is known to be unaffected by word frequency (Forster and Davis, 1984) and it is generally interpreted to reflect a “head-start” in orthographic processing (Gomez et al., 2013). The presence of a typical identity priming effect (e.g., the sizes of priming effects being ±10 ms of the prime duration, see Forster et al., 2003) would indicate participants’ ability to process masked primes in alphabetic script.

For the identity priming condition, a different set of 42 medium frequency targets were selected (M = 83.2 per million). The mean length of these targets was 4.4 letters (60% consisted of one syllable, 40% consisted of two syllables). Each target (e.g., SOFT) was primed either by the target itself (i.e., soft) or by a control prime that did not share any letters with the target at the same position (e.g., page). The mean word frequency and the mean length of the control primes were 74.3 per million and 4.4 letters. None of the words in the identity priming condition were used in the C/CV conditions. For the identity priming condition, there also were two counterbalanced lists in order to present the same targets to all participants but each participant saw only one of the prime-target pairings.

Apparatus and Procedure

Participants were tested individually using the DMDX software package (Forster and Forster, 2003). Each trial began with the presentation of a forward mask (#####) for 500 ms followed by a 50 ms presentation of a lower case prime. Immediately following the prime, a target was presented in upper case. The target remained on the display until the participant made a response. Participants were instructed to read aloud the target as quickly and accurately as possible. The stimuli were presented at the center of the screen in 12-pt Courier New font. The presence of primes was not mentioned to any participant. Participants completed 16 practice trials to familiarize themselves with the task.

For the C and CV priming conditions, the same set of 42 targets was presented twice, once in the C condition and once in the CV condition. The identity priming condition was always presented in between the C and CV conditions. Half of the participants were presented with the C condition in the first block, and the CV condition in the third block; the other half were presented with the CV condition in the first block, and the C condition in the third block. Targets primed by critical primes (either C or CV) in the first block were primed by control primes in the third block, and vice versa. Therefore, for the C/CV conditions, although there were two counterbalancing lists with regard to prime-target relationships (i.e., related vs. control), there were four presentation orders differing in whether the target was paired with an C prime or a CV prime first, crossed with the two lists.

Results

Raw naming reaction times (RTs) were checked using CheckVocal Software (Protopapas, 2007). We used a linear mixed-effect (LME) model (lme4; Baayen, 2008; Bates et al., 2008) implemented in R (R Development Core Team, 2008) to analyze RT for correct trials and error rates. lmerTest package in R was used to calculate the p-values using Satterthwaite’s approximation for the degrees of freedom (Kuznetsova et al., 2014). In order to meet the distributional assumptions of LME, we applied the inverse transformation to the RTs (–1000/RT) to better approximate normality in the RT distribution (see Box and Cox, 1964). Correct data points that were 3.5 SD away from the individual’s mean per condition were removed as outliers (both 0.3% of the data in the C/CV conditions and Identity condition, respectively). In the identity priming condition, three items (DENY, TINY, RIFLE) were removed due to high error rates (>55%).

For the C and CV conditions, the initial model included Overlap (CV vs. C), Prime Type (related vs. control) and Order (first vs. third block) and their interaction as fixed factors, and by-subject intercept and slope and by-item intercept and slope of Overlap, Prime Type, and their interaction as random factors. Note that Block 2 is not considered in the Order variable as it always contained the identity primes. Each of the categorical variables was contrast coded by 0.5/-0.5. We also entered the following target lexical characteristics as fixed factors: Log subtlex frequency (Brysbaert and New, 2009), Orthographic neighborhood size (Ortho-N), and Length. These continuous variables were centered around their respective means. In addition, because Length and Ortho-N were moderately correlated (r = 0.53), Ortho-N was regressed against Length and their residuals were used as a predictor for Ortho_N (i.e., res_Ortho-N). Thus the model used in the analyses was [invRT ∼ Overlap^∗PrimeType^∗Order + Log subtlex frequency + res_Ortho-N + Length + (1 + Overlap^∗ Prime Type| subject) + (1 + Overlap^∗Prime Type| target)].

For the identity priming condition, the model used in the analyses was the same as above except that Order was not included as a factor. For the C, CV and Identity conditions, errors were analyzed using a mixed-effects logistic model (Jaeger, 2008) using the same fixted factors used for RT analyses.⁴ However, the error rates were small and there were no significant priming effects in any conditions except in the identity condition (p = 0.02), therefore we will only report the results of response latencies analyses. Table 1 shows the mean RT and error rates for the three conditions. Table 1 shows the mean RT and error rates for the three conditions.

TABLE 1

TABLE 1. Mean naming latencies (ms) and percentage errors (%) for English targets primed by C primes, C control primes, CV primes, CV control primes, identity primes and identity control primes in Experiment 1, for low-proficient bilinguals.

Onset (C) and CV Priming Effects

Order did not significantly affect the patterns of priming as indicated by the lack of three-way interaction between Order, Overlap, Prime Type (t < 1) and also by the lack of two-way interaction between Order and Prime Type (t < 1). The main effect of Order was statistically significant (t = 5.10, p < 0.001); naming latencies were significantly faster in the third block than in the first block. The main effect of Prime Type was significant (t = 4.13, p < 0.001). The main effect of Overlap was not significant (t < 1). Importantly, there was a significant interaction between Overlap and Prime Type (t = 2.57, p = 0.014). Follow-up analyses of this interaction revealed that there was no C (onset) priming (t = 1.02, p > 0.10, a –2 ms difference; in contrast, there was a significant CV priming effect (t = 4.46, p < 0.001, a 25 ms effect). As for the effects of target lexical characteristics, there was a significant effect of Log subtlex frequency (t = –7.47, p < 0.001), Ortho-N (t = –3.76, p < 0.001), and Length (t = 4.23, p < 0.001), that is, faster naming latencies were associated with targets with higher frequency, more orthographic neighbors, and shorter lengths.

Identity Priming Effects

The effect of Prime type was significant (t = 8.05, p < 0.001); targets were named 41 ms faster when they were primed by identity words than by control words. This confirmed that low proficient bilinguals are able to process masked English primes sufficiently. The model also revealed a significant effect of Log subtlex frequency (t = –2.92, p < 0.01), and Length (t = 3.26, p < 0.01); higher frequency and shorter targets were associated with faster naming latency. The effect of Ortho_N was not significant (t < 1).

Discussion

The critical result of Experiment 1 was that low-proficient Japanese–English bilinguals did not show an onset priming effect for L2-English targets (e.g., bark-BENCH = dark-BENCH). This finding differs from the significant onset priming effects typically found in reading aloud with native speakers of European languages (e.g., Forster and Davis, 1991; Kinoshita, 2000; Schiller, 2004) or the result obtained in Verdonschot et al. (2013) with proficient Chinese–English bilinguals. The low-proficient bilinguals, nevertheless, showed significant CV (mora) priming (bell-BENCH < cell-BENCH). In fact, the absence of onset priming together with the presence of CV (mora) priming parallel those reported by Verdonschot et al. (2011) with Japanese native speakers reading aloud Japanese kana and romaji-transcribed words. These data taken together suggest that the low-proficient bilinguals carried over their L1 unit to L2 word production.

In Experiment 2, high-proficient Japanese–English bilinguals were tested. Based on the results of Verdonschot et al. (2013) who found significant onset priming with proficient Chinese–English bilinguals, we expect to replicate that finding.