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@INPROCEEDINGS{Ruvolo_ICASSP_SPADE_WORKSHOP_2025,
         author = {Ruvolo, Barbara and Purohit, Tilak and Vlasenko, Bogdan and Orozco-Arroyave, Juan Rafael and Magimai-Doss, Mathew},
       projects = {EMIL},
          title = {Exploring the Complexity of Parkinson’s Patient Speech for Depression Detection task: A Qualitative Analysis},
      booktitle = {Proceedings of Workshop on Speech Pathology Analysis and DEtection (SPADE)},
           year = {2025},
       abstract = {This study examines the acoustic features of Parkin-
son’s patients with depression. More specifically, the research
investigates whether interpretable, handcrafted acoustic feature-
based methods, previously used for automatic speech-based
depression detection, can be applied to detect depression in PD
patients. We approach this by conducting a comparative study
of speech-based depression detection tasks, using the DAIC-Woz
corpus for typical speech and the PD-Depression corpus for atyp-
ical speech. We investigate how the acoustic descriptors of typical
depressed speech differ from those extracted from the speech of
PD patients suffering from depression. Our finding indicates that
while typical depressed speech exhibits pronounced fluctuations
in pitch and vocal stability, the speech of Parkinson’s patients
presents a more varied range of spectral features, reflecting the
complexities of their condition caused by hypokinetic dysarthria.},
            pdf = {https://publications.idiap.ch/attachments/papers/2025/Ruvolo_ICASSP_SPADE_WORKSHOP_2025.pdf}
}