Bibliographic record
Abstract
Most acoustic work on sibilants has focused on English /s/ and /ʃ/, examining spectra of the middle portion of these consonants. Voiced sibilants, which are rarer cross-linguistically (Ohala, 1983), as well as sibilants in other languages, have received less attention; in particular, there has been no previous work on Quebec French. Previous cross-linguistic studies have suggested important differences in sibilant acoustics exist between languages (Gordon et al., 2002), including in the dynamics of spectral properties over the course of the segment (Reidy, 2016). This study adds to the literature on the typology of sibilant acoustics by examining the spectral dynamics of sibilants in Quebec French (/s, ʃ, z, ʒ/). ∼28 k word-initial, pre-vocalic tokens from more than 100 speakers are extracted from a large corpus of parliamentary speech (Milne, 2014). For each token, multitaper spectra (Reidy, 2013) over a 20 ms window are calculated at 17 equidistant points. A variety of acoustic measures, including segment duration and spectral moments, are reported. Preliminary results examining static measures reveal that the anterior sibilants have higher spectral speak (∼5700 Hz vs ∼4600 Hz for posterior ones), as expected; unlike in English, however, / s/ and /ʃ/ have similar average duration.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".