Bibliographic record
Abstract
This study reexamines perceptual epenthesis by Japanese listeners. It has been argued that since Japanese phonology prohibits consonant clusters Japanese listeners tend to perceive an illusionary vowel /u/ between consonants in a cluster so that their percepts conform to their native phonology. As a consequence, they do not perceive difference between strings like /VCCV/ and /VCuCV/. However, consonant clusters actually occur in natural speech in Japanese as a result of vowel deletion. Additionally, it has been shown that Japanese listeners are sensitive to acoustic difference between consonant clusters with a deleted vowel and their counterparts with an undeleted vowel. These observations raise a question about the above generalization. This study hypothesizes that the perceptibility of consonant clusters for Japanese listeners is determined not only by their phonological knowledge, but also by their phonetic knowledge about how likely certain types of consonant clusters occur in natural speech as a result of vowel deletion. In order to test the hypothesis, 19 Japanese listeners were tested on discrimination between consonant clusters and their counterparts with an intervening vowel /u/. Consonant clusters were classified into 4 ranked (lowest to highest) types according to the probability of their occurrence as a result of vowel deletion: voiced stop - voiced stop (DD), voiceless stop - voiced stop (TD), voiceless stop - voiceless stop (TT), voiceless fricative - voiceless stop (ST). The result showed that performance varied depending on cluster types. However, the variation did not follow the order of probability; performance was slightly better with TD and TT types than DD and ST types. The result also showed an effect of stimuli presentation order with TT type (Figure1). These findings are discussed in the light of phonological bias and general auditory speech processing. Figur 1
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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 | 0.000 | 0.000 |
| 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".