Detecting Alzheimer's Disease Using Gated Convolutional Neural Network from Audio Data

03/30/2018
by   Tifani Warnita, et al.
0

We propose an automatic detection method of Alzheimer's diseases using a gated convolutional neural network (GCNN) from speech data. This GCNN can be trained with a relatively small amount of data and can capture the temporal information in audio paralinguistic features. Since it does not utilize any linguistic features, it can be easily applied to any languages. We evaluated our method using Pitt Corpus. The proposed method achieved the accuracy of 73.6 (SMO) by 7.6 points.

READ FULL TEXT

Please sign up or login with your details

Forgot password? Click here to reset