Bibliographic record
Abstract
It has been claimed that Canadian raising (CR), in which certain diphthongs raise before voiceless consonants, arises from the shortening effect these consonants have on preceding vowels (Myers 1997). While CR is phonological and occurs regardless of speech rate, it is unknown to what extent it occurs in singing, in which large differences in note duration make it impossible to correct for speech rate. This question is particularly interesting for professional singers, who are trained to modify their vowels. Trained singers have been shown to have a significantly reduced vowel space (Ophaug 2010) and to maintain a more open jaw posture (Nair et al. 2016), which may interfere with raising. We report on an experiment in which Canadian singers are asked to say and sing passages containing multiple tokens of raising vowels followed by voiceless and voiced consonants. Tokens are embedded in novel lyrics written to fit commonly known melodies. We test the degree of raising in singing compared to speaking as well as within each of these production modes. Results contribute to our understanding of the acoustics of singing and how singer dialect interacts with the acoustic realization of the articulatory settings of trained singing. References: Myers, J. (1997). Canadian raising and the representation of gradient timing relations. Studies in the Linguistic Sciences, 27(1). Nair, A., Nair, G., & Reishofer, G. (2016). The Low Mandible Maneuver and Its Resonential Implications for Elite Singers. Journal of Voice, 30(1). Ophaug, W. (2010). Sangfonetikk: en innforing. Fagbokforlaget.
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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 | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.038 | 0.006 |
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".