MFCC-based Recurrent Neural Network for Automatic Clinical Depression Recognition and Assessment from Speech

no code implementations • 16 Sep 2019 • Emna Rejaibi, Ali Komaty, Fabrice Meriaudeau, Said Agrebi, Alice Othmani

The proposed approach outperforms the state-of-art approaches on the DAIC-WOZ database with an overall accuracy of 76. 27% and a root mean square error of 0. 4 in assessing depression, while a root mean square error of 0. 168 is achieved in predicting the depression severity levels.

Data Augmentation Transfer Learning