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- W3119787410 abstract "In voice therapy, assessment of pathological voice widely depends on subjective evaluation by clinicians and practitioners. This approach of voice evaluation is apparently prone to bias, especially for mildly dysphonic voices in which features are hard to distinguish. As such, research has been focused on objective and automatic estimation of the mildly dysphonic voices. In the present study, a multi-modality approach using six kinematic features and six acoustic features were examined. The pathological voices GO and G1 on the GRBAS scale was classified, and the best result (0.84 using SVM classifier) was achieved when combining features from both modalities. The findings indicated that the proposed method can be used as a reliable way to assess the mildly pathological voice." @default.
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- W3119787410 date "2020-12-04" @default.
- W3119787410 modified "2023-10-14" @default.
- W3119787410 title "Detecting Mild Pathological Voice based on Multi-modality Features" @default.
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- W3119787410 doi "https://doi.org/10.1109/ialp51396.2020.9310476" @default.
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