2026-05-01T21:09:57Z https://meral.edu.mm/oai

oai:meral.edu.mm:recid/3481 2022-03-24T23:14:59Z 1582963302567:1597824273898 user-ucsy

Depression Detection from Speech Emotion Recognition Mar, Lwin Lwin Pa, Win Pa The recognition of the internal emotional stateof a person plays an important role in several humanrelatedfields. Emotions constitute an essential part ofour existence as it exerts great influence on thephysical and mental health of people. Depression is acommon mental disorder. Developments in affectivesensing technology with focus on acoustic features willpotentially bring a change due to depressed patients’slow, hesitating, monotonous voice as remarkablecharacteristics. This paper will present classificationof emotions and from it, depression is detected byusing speech signals. Both time and frequency domainfeatures will be used in feature vector extraction. Infeature extraction, the paper will use wavelettransform and MFCC. DenseNet will be used to detectthe emotion, classify the type of emotion and thendepression. 2019-02-27 http://hdl.handle.net/20.500.12678/0000003481 https://meral.edu.mm/records/3481