Bibliographic record
Abstract
An utterance of a language often demonstrates the effect of declination, usually understood broadly as a reduction in certain physical or acoustic signals. Previous research on declination focuses primarily on the acoustic measures of pitch (such as the movement of pitch or the alternation of pitch span) or intensity. Neglected in the matter is the third acoustic dimension of speech duration. This paper reports on an experiment on declination focusing on pitch duration. The language studied is Mandarin Chinese. Six native Mandarin speakers are recruited. A total of 864 utterances of 2-to-9 syllables in four tones and four functional intonations are recorded and analyzed on Praat. The results show that the declination of pitch duration goes side by side along the pitch declination, both of which share the same physiological basis. Specifically, (1) the average pitch duration within the prosodic unit decreases gradually from the sentence-initial prosodic unit to the sentence-final one, (2) the pitch duration of the left-most syllable of the prosodic unit decreases gradually from the sentence-initial prosodic unit to the sentence-final one, and (3) the pitch duration of the right-most syllable of the prosodic unit decreases slightly from the sentence-initial prosodic unit to the sentence-final one.
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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 | 0.007 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".