Perceptual development of phonotactic features in Japanese infants
Bibliographic record
Abstract
Acceptable phonotactics differ among languages. Japanese does not allow consonant clusters except in special contexts and this phonotactic constraint has a strong effect on adults speech perception system. When two consonants follow one another in nonsense words, adult Japanese listeners hear illusory epenthetic vowels between the consonants. The current study is aimed at investigating the influence of language-specific phonotactic rules on infants’ speech perception development. Six-, 12-, and 18-month-old infants were tested on their sensitivity to phonotactic changes in words using a habituation-switch paradigm. The stimuli were three nonsense words: ‘‘keet (/ki:t/),’’ ‘‘keets (/ki:ts/),’’ and ‘‘keetsu (/ki:tsu/).’’ ‘‘Keetsu’’ perfectly follows Japanese phonotactic rules. ‘‘Keets’’ is also possible in devoicing contexts in fluent speech, but the acceptability of ‘‘keets’’ for adult native Japanese speakers is much less than ‘‘keetsu.’’ ‘‘Keet’’ is phonotactically impossible as a Japanese word. The results indicate the existence of a developmental change. Twelve months and older infants detected a change from the acceptable Japanese word ‘‘keetsu’’ to the possible but less acceptable word ‘‘keets.’’ However, discrimination between ‘‘keets’’ and the non-Japanese ‘‘keet’’ is seen only in 18-month infants. Implications for infants’ speech perception with relation to language specific phonotactical regularities will be discussed.
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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 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".