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Title
Japanese: 
English:Detecting Alzheimer's Disease Using Gated Convolutional Neural Network from Audio Data 
Author
Japanese: Warnita Tifani, 井上 中順, 篠田 浩一.  
English: Tifani Warnita, Nakamasa Inoue, Koichi Shinoda.  
Language English 
Journal/Book name
Japanese: 
English:Proc. Interspeech 2018 
Volume, Number, Page         pp. 1706-1710
Published date Sep 4, 2018 
Publisher
Japanese: 
English:ISCA 
Conference name
Japanese: 
English:Interspeech 2018 
Conference site
Japanese:ハイデラバード 
English:Hyderabad 
File
Official URL https://www.isca-speech.org/archive/Interspeech_2018/pdfs/1713.pdf
 
DOI https://doi.org/10.21437/Interspeech.2018-1713
Abstract 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%, which is better than the conventional sequential minimal optimization (SMO) by 7.6 points.

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