Articulatory correlates of voice qualities of god guys and bad guys in Japanese anime: an MRI study
Bibliographic record
Abstract
This paper examines the articulatory correlates of the Hero and Villain Voice Types, which were auditorily identified in a separate study on cartoon voices, using the magnetic resonance imaging (MRI) technique. In general, the MRI images were in good agreement with the previous auditory analysis results; the major characteristic difference between voice quality settings of heroes and those of villains and between two villainous voice types was found in the supraglottal states and the pharyngeal cavity. Auditory analysis can be as valid as acoustic or any other analysis method depending on the level of training in a commonly accepted system such as Laver’s framework for voice quality description. However, the MRI technique also allowed us to see what would not be observed otherwise, e.g., larynx height, pharyngeal cavity, vocal tract length, and the position of the hyoid bone. Auditory and physiological methods should be used in combination in order to further our understanding of the larynx and the pharynx.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".