Mar 15, 2023 · This study provides support for task design and classifier building for audio-based depression recognition, which could assist in mass screening for depression.
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This study provides support for task design and classifier building for audio-based depression recognition, which could assist in mass screening for depression.
The overall process of depression recognition consisted of five parts: preprocessing, feature extraction, dimension reduction, clas- sification and evaluation. ...
The paper explores the use of the AQJSM method, which is built upon combining the JSM and AQ methods, to identify cause-effect relationships between ...
The results showed that spontaneous pronunciation induced more significantly discriminative acoustic features and achieved better recognition performance ...
Nov 10, 2022 · This study provides support for task design and classifier building for audio-based depression recognition, which could assist in mass screening for depression.
An Automatic Depression Recognition Method from Spontaneous Pronunciation Using Machine Learning. https://doi.org/10.1145/3574198.3574219.
This study suggests that the analysis of speech data recorded while reading text-dependent sentences could help predict depression status automatically by ...
Missing: Pronunciation | Show results with:Pronunciation
Dec 15, 2020 · In this paper, we propose an Artificial Intelligence (AI) based application for clinical depression recognition and assessment from speech.
Jun 21, 2022 · This paper systematically and precisely outlines the most prominent and up-to-date research of automatic depression recognition by intelligent speech signal ...