Perception of vowels with missing formant peaks
Bibliographic record
Abstract
Although the first two or three formant frequencies are considered essential cues for vowel identification, certain limitations of this approach have been noted. Alternative explanations have suggested listeners rely on other aspects of the gross spectral shape. A study conducted by Ito, Tsuchida, and Yano [(2001). J. Acoust. Soc. Am. 110, 1141-1149] offered strong support for the latter, as attenuation of individual formant peaks left vowel identification largely unaffected. In the present study, these experiments are replicated in two dialects of English. Although the results were similar to those of Ito, Tsuchida, and Yano [(2001). J. Acoust. Soc. Am. 110, 1141-1149], quantitative analyses showed that when a formant is suppressed, participant response entropy increases due to increased listener uncertainty. In a subsequent experiment, using synthesized vowels with changing formant frequencies, suppressing individual formant peaks led to reliable changes in identification of certain vowels but not in others. These findings indicate that listeners can identify vowels with missing formant peaks. However, such formant-peak suppression may lead to decreased certainty in identification of steady-state vowels or even changes in vowel identification in certain dynamically specified vowels.
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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 | 0.004 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".