{"ID":2860551,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2510.03758","arxiv_id":"2510.03758","title":"Cross-Lingual Multi-Granularity Framework for Interpretable Parkinson's Disease Diagnosis from Speech","abstract":"Parkinson's Disease (PD) affects over 10 million people worldwide, with speech impairments in up to 89% of patients. Current speech-based detection systems analyze entire utterances, potentially overlooking the diagnostic value of specific phonetic elements. We developed a granularity-aware approach for multilingual PD detection using an automated pipeline that extracts time-aligned phonemes, syllables, and words from recordings. Using Italian, Spanish, and English datasets, we implemented a bidirectional LSTM with multi-head attention to compare diagnostic performance across the different granularity levels. Phoneme-level analysis achieved superior performance with AUROC of 93.78% +- 2.34% and accuracy of 92.17% +- 2.43%. This demonstrates enhanced diagnostic capability for cross-linguistic PD detection. Importantly, attention analysis revealed that the most informative speech features align with those used in established clinical protocols: sustained vowels (/a/, /e/, /o/, /i/) at phoneme level, diadochokinetic syllables (/ta/, /pa/, /la/, /ka/) at syllable level, and /pataka/ sequences at word level. Source code will be available at https://github.com/jetliqs/clearpd.","short_abstract":"Parkinson's Disease (PD) affects over 10 million people worldwide, with speech impairments in up to 89% of patients. Current speech-based detection systems analyze entire utterances, potentially overlooking the diagnostic value of specific phonetic elements. We developed a granularity-aware approach for multilingual PD...","url_abs":"https://arxiv.org/abs/2510.03758","url_pdf":"https://arxiv.org/pdf/2510.03758v1","authors":"[\"Ilias Tougui\",\"Mehdi Zakroum\",\"Mounir Ghogho\"]","published":"2025-10-04T09:51:00Z","proceeding":"cs.CL","tasks":"[\"cs.CL\",\"cs.SD\",\"eess.AS\"]","methods":"[]","has_code":false,"code_links":[{"ID":608739,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_id":2860551,"paper_url":"https://arxiv.org/abs/2510.03758","paper_title":"Cross-Lingual Multi-Granularity Framework for Interpretable Parkinson's Disease Diagnosis from Speech","repo_url":"https://github.com/jetliqs/clearpd","is_official":false,"mentioned_in_paper":false,"mentioned_in_github":true,"github_stars":0}]}