The role of prevoicing, breathy-voicing and aspiration in the perception of breathy-voiced stops in Bangla
Bibliographic record
Abstract
Abstract This study investigated the role of prevoicing, breathy-voicing, and plain-aspiration in the perception of the voiced-aspirated stop category in Bangla. 31 native speakers of Bangla undertook two different perception experiments where they had to identify what stop category they can hear in forced-choice MCQ tasks. Each experiment presented 25 stimuli (repeated 3 times) that were artificially manipulated; stimuli in Experiment-1 were manipulated for the duration of prevoicing and breathy-interval, while stimuli in Experiment-2 were manipulated for the duration of prevoicing and plain-aspiration. A total of 4650 response tokens were collected in two experiments. Results revealed that a prevoicing interval of about 40ms and a breathy interval of about 20–40 ms are required for the perception of voiced-aspirates. In addition, listeners showed a clear preference for breathy-voicing over plain-aspiration when categorizing sounds as voiced-aspirated stop, indicating that breathy-voicing is perceived to be better associated with voiced-aspirates. Implications for the general phonetics of voiced-aspirates are discussed in the light of the results.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".