Easy detection of rare dementia based on speech analysis

Shunya Hanai, Shohei Kato, Koichi Sakaguchi, Takuto Sakuma, Reiko Ohdake, Michihito Masuda, Hirohisa Watanabe

研究成果: Conference contribution

1 被引用数 (Scopus)

抄録

The increase in the number of dementia patients is a serious problem in developed countries. It is important to diagnose an underlying disease correctly because dementia has treatments depending on the disease. We have been investigating frontotemporal lobar degeneration (FTLD), which is one of the underlying diseases. This paper presents a speech analysis-based FTLD screening system. We used speech features to classify FTLD, Alzheimer's disease (AD) and HC. We confirmed that our method can classify three groups with accuracy of 0.81 and macro F-measure of 0.74. Our screening system has the potential to detect FTLD through short speech.

本文言語English
ホスト出版物のタイトル2020 IEEE 9th Global Conference on Consumer Electronics, GCCE 2020
出版社Institute of Electrical and Electronics Engineers Inc.
ページ954-956
ページ数3
ISBN(電子版)9781728198026
DOI
出版ステータスPublished - 13-10-2020
イベント9th IEEE Global Conference on Consumer Electronics, GCCE 2020 - Kobe, Japan
継続期間: 13-10-202016-10-2020

出版物シリーズ

名前2020 IEEE 9th Global Conference on Consumer Electronics, GCCE 2020

Conference

Conference9th IEEE Global Conference on Consumer Electronics, GCCE 2020
国/地域Japan
CityKobe
Period13-10-2016-10-20

All Science Journal Classification (ASJC) codes

  • 信号処理
  • 電子工学および電気工学
  • メディア記述
  • 器械工学
  • コンピュータ ネットワークおよび通信
  • コンピュータ ビジョンおよびパターン認識

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