Context effects on the perception of vowel spectral properties
Bibliographic record
Abstract
Previous studies [M. Kiefte and K. R. Kluender, J. Acoust. Soc. Am. 57, 55–62 (2001)] have shown that long-term stationary spectral characteristics have a very strong influence on the perception of specific cues in monophthongs. For example, F2 will be perceptually neglected if a precursor sentence is filtered by a one-pole filter corresponding to the center frequency and bandwidth of the target vowel. The present work continues this research and presents results from experiments using nonspeech precursors. The first set of experiments use speechlike stimuli that have been LPC vocoded from a time-reversed sentence having similar spectro-temporal properties to natural speech. The second set of experiments use FM-formant glides as precursors to test multiple hypotheses including the time course of these effects over varying precursor durations. The second set of experiments also test the hypothesis that the duration of the precursor plays a role in the magnitude of the context effect on the perception of the following vowel.
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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 | 0.003 |
| 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 | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".