Examining the extent of anticipatory coronal coarticulation: A long-term average spectrum analysis
Bibliographic record
Abstract
Phonetic studies of English liquids /r/ and /l/ have shown these consonants can exert strong coarticulatory effects on both adjacent and non-adjacent vowels. The current study investigated local and long-range effects of coronals /l/, /r/, and /d/ in Canadian English. Fourteen speakers were recorded reading the sentences 'We thought it might be a ram/lamb/dam/ham'. Formants F1-F3 and long-term average spectra (LTAS) of 5 vowels preceding the target consonants were calculated and compared to baseline values. The results revealed significant differences between the coronal consonants and the control (/h/) in up to 4 preceding syllables. Formant differences in non-adjacent syllables were limited to F3 (lower for /r/ than the other consonants) and were attenuated in stressed syllables. Non-adjacent LTAS differences were overall more robust, but primarily differentiated between coronals and the non-coronal /h/. Overall, /r/ showed the greatest effect on non-adjacent preceding vowels, followed by /l/, and then by /d/. The formant and LTAS methods appear to capture somewhat different, yet equally important aspects of local and long-range coarticulation. The LTAS findings suggest that higher-frequency information, while generally disregarded for speech, may contain significant coarticulatory information.
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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 | 0.000 | 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 | 0.000 |
| 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".