Relative importance of speech and voice features in the classification of schizophrenia and depression.

ABSTRACT: Speech is a promising biomarker for schizophrenia spectrum disorder (SSD) and major depressive disorder (MDD). This proof of principle study investigates previously studied speech acoustics in combination with a novel application of voice pathology features as objective and reproducible classifiers for depression, schizophrenia, and healthy controls (HC). Speech and voice features for classification were calculated from recordings of picture descriptions from 240 speech samples (20 participants with SSD, 20 with MDD, and 20 HC each with 4 samples). Binary classification support vector machine (SVM) models classified the disorder groups and HC. For each feature, the permutation feature importance was calculated, and the top 25% most important features were used to compare differences betwee

SUBMITTER: Berardi M 

PROVIDER: S-EPMC10509176 | biostudies-literature | 2023 Sep

REPOSITORIES: biostudies-literature