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Machine-learning methods using acoustic features in the diagnosis of major depressive disorder (MDD) have insufficient evidence from large-scale samples and clinical trials. This study aimed to evaluate the effectiveness of the promising i-vector method on a large sample of women with recurrent MDD diagnosed clinically, examine its robustness, and provide an explicit acoustic explanation of the i-vectors. We collected utterances edited from clinical interview speech records of 785 depressed and 1,023 healthy individuals. Then, we extrac
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