{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,27]],"date-time":"2026-10-27T22:59:23Z","timestamp":1793141963382,"version":"4.5.0"},"reference-count":75,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2025,10,29]],"date-time":"2025-10-29T00:00:00Z","timestamp":1761696000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"NSF-National Science Foundation","award":["852 2037266\u2014SenSE"],"award-info":[{"award-number":["852 2037266\u2014SenSE"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Brain Sciences"],"abstract":"<jats:p>Background\/Objectives: Parkinson\u2019s disease (PD) affects both articulatory and phonatory subsystems, leading to characteristic speech changes known as hypokinetic dysarthria. However, few studies have jointly analyzed these subsystems within the same participants using interpretable deep-learning-based measures. Methods: Speech data from the PC-GITA corpus, including 50 Colombian Spanish speakers with PD and 50 age- and sex-matched healthy controls were analyzed. We combined phonological feature posteriors\u2014probabilistic indices of articulatory constriction derived from the Phonet deep neural network\u2014with harmonics-to-noise ratio (HNR) as a laryngeal measure. Linear mixed-effects models tested how these measures related to disease severity (UPDRS, UPDRS-speech, and Hoehn and Yahr), age, and sex. Results: PD participants showed significantly higher [continuant] posteriors, especially for dental stops, reflecting increased spirantization and articulatory weakening. In contrast, [sonorant] posteriors did not differ from controls, indicating reduced oral constriction without a shift toward more open, approximant-like articulations. HNR was predicted by vowel height and sex but did not distinguish PD from controls, likely reflecting ON-medication recordings. Conclusions: These findings demonstrate that deep-learning-derived articulatory features can capture early, subphonemic weakening in PD speech\u2014particularly for coronal consonants\u2014while single-parameter laryngeal indices such as HNR are less sensitive under medicated conditions. By linking spectral energy patterns to interpretable phonological categories, this approach provides a transparent framework for detecting subtle articulatory deficits and developing feature-level biomarkers of PD progression.<\/jats:p>","DOI":"10.3390\/brainsci15111162","type":"journal-article","created":{"date-parts":[[2025,10,29]],"date-time":"2025-10-29T17:38:22Z","timestamp":1761759502000},"page":"1162","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Speech Markers of Parkinson\u2019s Disease: Phonological Features and Acoustic Measures"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7471-1177","authenticated-orcid":false,"given":"Ratree","family":"Wayland","sequence":"first","affiliation":[{"name":"Department of Linguistics, University of Florida, Gainesville, FL 32611, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rachel","family":"Meyer","sequence":"additional","affiliation":[{"name":"Department of Linguistics, University of Florida, Gainesville, FL 32611, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7382-9344","authenticated-orcid":false,"given":"Kevin","family":"Tang","sequence":"additional","affiliation":[{"name":"Department of Linguistics, University of Florida, Gainesville, FL 32611, USA"},{"name":"Department of English Language and Linguistics, Institute of English and American Studies, Faculty of Arts and Humanities, Heinrich Heine University D\u00fcsseldorf, 40225 D\u00fcsseldorf, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2025,10,29]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"57","DOI":"10.1038\/s41531-025-00913-4","article-title":"Speech and language biomarkers for Parkinson\u2019s disease prediction, early diagnosis and progression","volume":"11","author":"Cao","year":"2025","journal-title":"npj Park. 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