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This study aimed to identify possible gender- or language-related differences in speech between men and women with multiple system atrophy (MSA). A total of 42 male and 40 female MSA patients, along with 41 male and 41 female age-matched healthy controls, were recruited from two centres representing two distinct languages: Czech and Italian. A quantitative acoustic assessment was performed using 12 distinct speech dimensions. No significant clinical differences in MSA patients were found between men and women in terms of age, disease duration, motor severity, or dysarthria severity. MSA patients exhibited significantly worse performance compared to controls for voice quality, pitch breaks, frequency and amplitude vocal tremor, slow and irregular sequential motion rates, imprecise consonants, dynamics of articulation, monopitch, excessive loudness variation, articulation rate, and inappropriate silences (\n                    <jats:italic>p<\/jats:italic>\n                    \u2009&lt;\u20090.001). Considering the gender-specific patterns, the female MSA patients manifested more impaired voice quality (\n                    <jats:italic>p<\/jats:italic>\n                    \u2009&lt;\u20090.05) and more frequent vocal tremor (\n                    <jats:italic>p<\/jats:italic>\n                    \u2009&lt;\u20090.05) then male MSA, while male MSA patients showed slower diadochokinetic rate (\n                    <jats:italic>p<\/jats:italic>\n                    \u2009&lt;\u20090.01) and higher excessive loudness variability (\n                    <jats:italic>p<\/jats:italic>\n                    \u2009&lt;\u20090.01) than female MSA. The impact of language on disease-related changes appears to be minimal for the majority of acoustic parameters considered. Despite some gender differences, our findings demonstrate that speech-based digital biomarkers in MSA offer high discriminatory power while maintaining good consistency across gender and language.\n                  <\/jats:p>","DOI":"10.1007\/s00702-025-03016-9","type":"journal-article","created":{"date-parts":[[2025,9,23]],"date-time":"2025-09-23T05:11:22Z","timestamp":1758604282000},"page":"449-459","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Speech impairment in a large sample of patients with multiple system atrophy: effect of gender and language"],"prefix":"10.1007","volume":"133","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1156-3709","authenticated-orcid":false,"given":"Tereza","family":"Tykalova","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jan","family":"Rusz","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiri","family":"Klempir","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Maria Teresa","family":"Pellecchia","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,9,23]]},"reference":[{"key":"3016_CR1","doi-asserted-by":"publisher","first-page":"9565","DOI":"10.1007\/s11042-021-11439-1","volume":"82","author":"M Biswas","year":"2023","unstructured":"Biswas M, Rahaman S, Ahmadian A et al (2023) Automatic spoken Language identification using MFCC based time series features. 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