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Hierarchical attention interpretation: an interpretable speech-level transformer for bi-modal depression detection
Depression is a common mental disorder. Automatic depression detection tools using speech, enabled by machine learning, help early screening of depression. This paper addresses two limitations that may hinder the clinical implementations of such tools: noise resulting from segment-level labelling an
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