Creaky Voice in Canadian English: An Acoustics-Focused Method
Bibliographic record
Abstract
Creaky voice is a voice quality attributed to vocal fold compression without complete glottal closure. Acoustically, it is characterized by three key properties: a low pitch, irregular vocal pulses, and decreased transglottal airflow. Previous work provides competing evidence of gender differences with regard to creaky voice in English: some studies find more creak in men's speech (Henton & Bladon, 1988; Klatt & Klatt, 1990) whereas more recent studies frequently report increased creakiness among women (Podesva, 2013; Yuasa, 2010). Many of the existing sociophonetic studies of creaky voice rely on impressionistic (auditory or visual) coding which are vulnerable to important perceptual biases (Davidson, 2019; White et al., 2022). Moreover, while creaky voice is attested in many varieties of English, comprehensive studies of creak in Canadian English are rare. This study is an acoustic analysis of creaky voice across gender in Canadian English. Three acoustic correlates of creak were extracted at vowel mid-points: a spectral slope measure, H1*-H2*, and two Harmonics-to-Noise Ratios (HNRs), cepstral peak prominence (CPP) and HNR at the lowest frequency band (0-500Hz). Spectral slopes are acoustic indicators of glottal constriction, lower spectral slope measures correlating with a more constricted glottis (reduced airflow) and therefore more creakiness. HNRs are measures of waveform periodicity with lower HNRs corresponding to higher levels of noise/aperiodic vibration which is also a typical property of creak. Linear mixed-effect models tested differences within each acoustic measure of creak in relation to social and linguistic factors. Results reveal that men's vowels have less reliable f0 tracks, lower H1*-H2* values and lower HNRs (CPP and HNR05) than women's vowels (Figure 1), presenting substantial evidence for more creakiness in men's speech. Overall, this study highlights the importance of acoustic measures in quantifying creak and provides new insight into the relation between creaky voice and gender.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".