Japanese EFL Learners’ production of pronouns and articles in English: Evidence for L2 Prosodic Structures
Bibliographic record
Abstract
Experimental studies on Japanese speakers of L2 English have revealed that L1 prosodic transfer is observed in the production of lexical accent, duration, and temporal organization across syllables (Ueyama 2000), and syllable structures and isochrony (Kubozono 1989). The whole intonation of L2 English may also be influenced by word order (Nespor et al. 2008) and phrasing (Selkirk & Tateishi 1991, Ito & Mester 2013). But it remains unclear how linguistic categories unavailable in L1 are realized prosodically. The current study investigated how morphosyntactic components unavailable in L1 Japanese are prosodically realized in L2 English. Twenty Japanese university students (intermediate level) and ten speakers of North American English participated in the study. Their task was to read a short passage aloud. A sample token is shown in the narrative (1). (1) Some years ago, Mr. Sato had [a very kind student] in [his class]. She had [a pretty name], Aika. [Her classmates] [liked her] very much. Sometimes Mr. Sato [saw her] at school early in [the morning]. In [her hands] [she always had very pretty flowers]. [She [picked them] from [her garden]]. Everyone in [her class] loved [the colorful flowers]. The personal pronouns and articles underlined above, whose equivalents are not available in Japanese, were selected for this acoustic analysis. The pitch and duration of these words and the pause afterwards were measured, the ratios to the relevant noun/verb phrases containing them were calculated, and compared with those of L1 English. The results revealed that the L2 learners tended to produce them with not only higher pitch and longer duration but also longer pause afterwards, resulting in the unexpected intervention of syntactic constituents in the sentences. A further analysis will be provided between L1 and L2 data in order to explore the nature of L1 prosodic transfer.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".