Understanding the developing sound system: interactions between sounds and words
Bibliographic record
Abstract
UNLABELLED: Over the course of the first 2 years of life, infants are learning a great deal about the sound system of their native language. Acquiring the sound system requires the infant to learn about sounds and their distributions, sound combinations, and prosodic information, such as syllables, rhythm, and stress. These aspects of the phonological system are being learned simultaneously as the infant experiences the language around him or her. What binds all of the phonological units is the context in which they occur, namely, words. In this review, we explore the development of phonetics and phonology by showcasing the interactive nature of the developing lexicon and sound system with a focus on perception. We first review seminal research in the foundations of phonological development. We then discuss early word recognition and learning followed by a discussion of phonological and lexical representations. We conclude by discussing the interactive nature of lexical and phonological representations and highlight some further directions for exploring the developing sound system. WIREs Cogn Sci 2014, 5:589-602. doi: 10.1002/wcs.1307 For further resources related to this article, please visit the WIREs website. CONFLICT OF INTEREST: The authors have declared no conflicts of interest for this article.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".