Contrastive tongue shapes of the three sibilant fricatives in Taiwan Mandarin read speech
Bibliographic record
Abstract
This study investigates the production of three sibilant fricatives in Taiwan Mandarin, dental [s], retroflex [?], and alveolopalatal [?], using ultrasound recording. Previous studies have pointed out that the contrast between dental [s] and retroflex [?] tends to be lost in connected speech in Taiwan Mandarin [1, 2]. We ask whether the merger could happen in read speech as well. Two Taiwan Mandarin speakers (1 male and 1 female) read a list of nonse words, which contained one of the three fricatives, followed by one of three vowels [a], [?], and [o]. Tongue shape was traced at the mid-point of each fricative and SSANOVA was used to compare the three fricatives. The analysis revealed two major points. (1) In read speech, both speakers made clearly distinguishable tongue shapes for all of the three fricatives, suggesting that speaking style plays a role in determining the likelihood of the merger; however, more data are required for further verification. (2) The amount of variation in tongue shape in different vowel contexts changed between speakers and fricatives. Speaker 1 showed a large amount of variation in the shape of the tongue body for dental [s], but not for retroflex [?] and alveolopalatal [?], while speaker 2 showed no such variation for any of the three fricatives. The pattern of variation made by speaker 1 conformed to previous observations that dental fricative requires an active engagement of the tongue tip but not the other part of the tongue, which remains flexible to coarticulate with the following vowels. Post-alveolar fricatives, however, require the active engagement of the whole tongue, which limits the possibility of coarticulation [3]. For both speakers, across vowel contexts, bunched tongue shape was observed for retroflex [?] and an advancement of the tongue root was observed for alveolopalatal [?].
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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 | 0.000 |
| 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".