Vowel Space, Variability, and Lexical Context in Infant Speech Perception
Bibliographic record
Abstract
Infant-directed speech (IDS) differs from adult-directed speech (ADS) in a number of phonetic dimensions, including mean pitch, pitch range, and speech rate (Fernald et al., 1989). Studies also find that the vowel space, as defined by centroids of the first and second formants for point vowels /i/, /u/, and /a/, is expanded in IDS as compared to ADS (e.g. Burnham et al., 2002; Kuhl et al., 1997; Liu et al., 2003). This expansion, when found in caregivers’ speech, is correlated with improved infant performance on discrimination tasks (Liu et al., 2003) and vocabulary tests (Hartman et al., 2017). Studies also find that individual vowels in IDS are more variable than in ADS, leading to reduced distances between vowel categories in the vowel space (e.g. Cristia & Seidl, 2014; McMurray et al., 2013). In Chapter 2, I explore the speech input of infants learning their first language in terms of the properties of IDS and ADS. I analyze naturalistic speech productions by mothers of 7-month-old or 15-month-old infants to determine whether vowel space expansion in IDS leads to easier categorization of vowels despite increases in variability of individual vowels, and whether this pattern changes depending on addressee age. In Chapter 3, I explore lexical context as a mechanism by which infants might interpret ambiguous vowels in their speech environment. Studies find that adults’ interpretation of ambiguous sounds can be biased by their lexical context, leading to shifted perception of ambiguous sounds outside of that lexical context (e.g. Norris et al., 2003). I expose infants to vowels that are perceptually ambiguous between /i/ and /ɪ/, in familiar words which are intended to bias interpretation of those sounds, in order to determine whether infants can use context as a means to resolve variability in IDS. I find that statistically speaking, there is no advantage of IDS vowels in terms of their categorizability, and that infants do not show a shift in their perception of ambiguous vowels based on context. I discuss the implications of these findings and future directions that could be taken to illuminate them in Chapter 4.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.022 | 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; both teacher heads agree on what is shown here.
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".