Perception and Production of Canadian English Vowels by L1 Spanish Speakers
Bibliographic record
Abstract
The present study investigates the perception and production of Canadian English (CE) vowels by L1 Spanish speakers who began acquisition of CE as adults. The objective was to determine which CE vowels will be difficult for Spanish speakers to discriminate and how this may affect the ability to produce the same vowel in a nativelike fashion. To this end, the perception and production of the CE phonemic monophthongs ∕i, i, e, ε, A, æ, α, o, u, u∕ by two groups was compared: A group of L1 Spanish, L2 Canadian English (CE) end-state speakers who began acquisition of English as adults (n = 11) and a group of native English speakers (n = 9). Participants were asked to perform a perception task and a production task. The perception task was a rhyming task in which participants were presented with an auditory stimulus word and asked to indicate which word from a list they felt the stimulus rhymed with. The list of possible response words contained one monosyllabic word of the type CVC for each of the ten CE vowels of interest. Both groups were asked to perform this task. The production task consisted of two reading lists, one of Spanish words and one of English words. The reading lists contained six words meant to elicit each of the ten CE monophthongs and each of the five Spanish monophthongs ∕a, e, i, o, u/. The L2 CE group was asked to read both lists and the L1 CE group was asked to read only the Enghsh word list. Results indicate that production is not necessarily indicative of perception. In three cases, vowels were produced based on orthographie representation and not primary linguistic data. The CE vowels /ι, ε, α∕ are perceived as variants of Spanish ∕e, a, a/ respectively, yet they are produced as variants of Spanish /i, e, o/. In each case, the CE vowel is pronounced as an instance of the Spanish vowel which would be indicated by the vowel grapheme used in the Enghsh reading list. These results call into question some vowel contrasts traditionally thought to be problematic, specifically ∕i∕-∕ι∕ and ∕ε∕-∕e∕. Also, the possibility of a paralinguistically motivated perception-production misalignment calls into question any phonological theory in which the symbolic units of representation are primarily auditory or gestural in nature.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".