Articulation and acoustics of Kannada affricates: A case of geminate /ʧ/
Bibliographic record
Abstract
Affricates have been observed to be problematic in phonological acquisition and disordered speech across languages, due to their relatively complex spatial and temporal articulatory patterns. Remediation of difficulties in the production of affricates requires understanding of how these sounds are typically produced. This study presents the first systematic articulatory and acoustic investigation of voiceless geminate affricate /ʧ/ in Kannada (a Dravidian language), compared to the palatal glide and the voiceless dental stop. Ultrasound data from 10 normal speakers from Mysore, India revealed that /ʧ/ is produced with the tongue shape intermediate between the palatal glide and the dental stop, and with the laminal constriction at the alveolar ridge. The observed articulatory differences are reflected in acoustic formant patterns of vowel transitions and stop/affricate bursts. Altogether, the results show that the Kannada consonant in question is an alveolopalatal affricate, supporting some of the previous descriptive phonetic accounts of the language and raising questions for further research on normal and disordered speech. The results and our survey of literature also suggest that affricates in South Asian languages tend to be phonetically variable and historically unstable compared to other consonant articulations.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".