Abstract
Purpose: This study evaluated whether articulatory kinematics, inferred by artic-ulatory phonology speech inversion neural networks, aligned with perceptual ratings of/ɹ/and/s/in the speech of children with speech sound disorders. Method: Articulatory phonology vocal tract variables were inferred for 5,961 utterances from 118 children and three adults, aged 2.25–45 years. Perceptual ratings were standardized using the novel 5-point PERCEPT Rating Scale and training protocol. Two research questions examined if the articulatory patterns of inferred vocal tract variables aligned with the perceptual error category for the phones investigated (e.g., tongue tip is more anterior in dentalized/s/pro-ductions than in correct/s/). A third research question examined if gradient PERCEPT Rating Scale scores predicted articulatory proximity to correct productions. Results: Estimated marginal means from linear mixed models supported 17 of 18/ɹ/hypotheses, involving tongue tip and tongue body constrictions. For/s/, estimated marginal means from a second linear mixed model supported seven of 15 hypotheses, particularly those related to the tongue tip. A third linear mixed model revealed that PERCEPT Rating Scale scores significantly predicted articulatory proximity of errored phones to correct productions. Conclusions: Inferred vocal tract variables differentiated category and magni-tude of articulatory errors for/ɹ/, and to a lesser extent for/s/, aligning with per-ceptual judgments. These findings support the clinical interpretability of speech inversion vocal tract variables and the PERCEPT Rating Scale in quantifying articulatory proximity to the target sound, particularly for/ɹ/.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 541-561 |
| Number of pages | 21 |
| Journal | Journal of Speech, Language, and Hearing Research |
| Volume | 69 |
| Issue number | 2 |
| DOIs | |
| State | Published - Feb 2026 |
Bibliographical note
Publisher Copyright:© 2026 American Speech-Language-Hearing Association.
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This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 4 Quality Education
PubMed: MeSH publication types
- Journal Article
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