2024-03-28T13:38:54Z
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