人工知能学会論文誌
Online ISSN : 1346-8030
Print ISSN : 1346-0714
ISSN-L : 1346-0714
速報論文
高齢者音声韻律特徴を用いたHDS-Rスコアとの相関分析
音声を用いた認知症の早期スクリーニングをめざして
加藤 昇平鈴木 祐太小林 朗子小島 敏昭伊藤 英則本間 昭
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2011 年 26 巻 2 号 p. 347-352

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This paper presents a new trial approach to early detection of cognitive impairment in the elderly with the use of speech sound analysis and multivariate statistical technique. In this paper, we focus on the prosodic features from speech sound. Japanese 115 subjects (32 males and 83 females between ages of 38 and 99) participated in this study. We collected speech sound in a few segments of dialogue of HDS-R examination. The segments corresponds to speech sound that is answering for questions on time orientation and number backward count. Firstly, 130 prosodic features have been extracted from each of the speech sounds. These prosodic features consist of spectral and pitch features (53), formant features (56), intensity features (19), and speech rate and response time (2). Secondly, these features are refined by principal component analysis and/or feature selection. Lastly, we have calculated speech prosody-based cognitive impairment rating (SPCIR) by multiple linear regression analysis. The results indicated that there is moderately significant correlation between HDS-R score and synthesis of several selected prosodic features. Consequently, adjusted coefficient of determination R2=0.50 suggests that prosody-based speech sound analysis has possibility to screen the elderly with cognitive impairment.

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© 2011 JSAI (The Japanese Society for Artificial Intelligence)
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