The Bidirectional Acquisition of Oral and Nasal Gestural Timing in L2 Brazilian Portuguese and Rioplatense Spanish Nasal Structures
Bibliographic record
Abstract
Brazilian Portuguese (BP) nasal vowels (Ṽᴺ) and Rioplatense Spanish (RS) vowel + nasal sequences (VN) are realized with two oral (vowel and consonant) gestures and a nasal (velum) gesture, but they differ in the way these gestures are sequenced. Adult native speakers of RS and BP who aim to acquire the opposite language will thus need to learn this cross-linguistic difference. On the one hand, non-native speakers of BP will have to realize a longer overlap of the vowel and velum gestures and a shorter nasal coda. On the other hand, non-native speakers of RS will need to produce a shorter gestural overlap and a longer nasal coda. The main purpose of this dissertation is to investigate the relative difficulties that RS and BP speakers encounter at the phonetic and phonological levels when acquiring the gestural pattern of the other language’s nasal structure. To accomplish this goal, four studies were conducted. The findings from the studies on monolingual and bilingual production suggest that nasal structures in RS and BP are similar but differ in terms of their gestural timing and that their phonetic implementation and phonological representation may be affected by the dominant language of heritage speakers. Moreover, the studies on naïve and L2 perception and production indicate that, with experience in the L2, the timing of the oral-nasal gestural overlap can be acquired by non-native speakers. However, the gestural timing of a longer nasal coda seems more difficult to realize than that of a shorter nasal coda, not only at first exposure but also with more experience in the L2. This suggests that nasal coda weakening, a common phonological process in language variation and change, poses less articulatory difficulties to L2 learners than nasal coda strengthening. We propose that a gestural timing constraint on nasal coda strengthening should be integrated into L2 models of phonological acquisition to better predict and explain relative difficulties encountered by L2 learners.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".