A generalizable speech emotion recognition model reveals depression and remission.

Hansen, Lasse; Zhang, Yan-Ping; Wolf, Detlef; Sechidis, Konstantinos; Ladegaard, Nicolai; Fusaroli, Riccardo

Hansen, Lasse; Zhang, Yan-Ping; Wolf, Detlef; Sechidis, Konstantinos; Ladegaard, Nicolai; Fusaroli, Riccardo.

Afiliación

Hansen L; Department of Clinical Medicine, Aarhus University, Aarhus, Denmark.
Zhang YP; Department of Affective Disorders, Aarhus University Hospital - Psychiatry, Aarhus, Denmark.
Wolf D; Center for Humanities Computing Aarhus, Aarhus University, Aarhus, Denmark.
Sechidis K; Roche Pharmaceutical Research & Early Development Informatics, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd., Basel, Switzerland.
Ladegaard N; Roche Pharmaceutical Research & Early Development Informatics, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd., Basel, Switzerland.
Fusaroli R; Roche Pharmaceutical Research & Early Development Informatics, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd., Basel, Switzerland.

Acta Psychiatr Scand ; 145(2): 186-199, 2022 02.

Article en En | MEDLINE | ID: mdl-34850386

Asunto(s)

Trastorno Depresivo Mayor; Habla; Depresión; Trastorno Depresivo Mayor/terapia; Emociones; Humanos; Aprendizaje Automático

Palabras clave

depression; machine learning; speech acoustics; speech emotion recognition; transfer learning

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Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Habla / Trastorno Depresivo Mayor Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Revista: Acta Psychiatr Scand Año: 2022 Tipo del documento: Article País de afiliación: Dinamarca

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