基于语音停顿度和平坦度的注意缺陷与多动障碍自动检测算法  

Automatic detection algorithm for attention deficit/hyperactivity disorder based on speech pause and flatness

作　　者：李国中 崔娅 俄木依欣 何凌[1] 李元媛[2] 熊熙 LI Guozhong;CUI Ya;EMU Yixin;HE Ling;LI Yuanyuan;XIONG Xi(College of Electrical Engineering,Sichuan University,Chengdu Sichuan 610065,China;Mental Health Center,West China Hospital of Sichuan University,Chengdu Sichuan 610065,China;School of Cyberspace Security,Chengdu University of Information Technology,Chengdu Sichuan 610025,China)

机构地区：[1]四川大学电气工程学院,成都610065 [2]四川大学华西医院心理卫生中心,成都610065 [3]成都信息工程大学网络空间安全学院,成都610225

出　　处：《计算机应用》2022年第9期2917-2925,共9页journal of Computer Applications

基　　金：国家自然科学基金资助项目(81901389);四川省科技计划项目(2019YFS0236)。

摘　　要：针对注意缺陷与多动障碍(ADHD)临床诊断主要依靠医生主观评估,缺乏客观辅助依据的问题,提出了一种基于语音停顿度和平坦度的ADHD自动检测算法。首先,通过频带差能熵积(FDEEP)参数自动定位语音有话区间,并提取停顿度特征;然后,使用变换平均幅度平方差(TAASD)参数计算语音倍频率,并提取平坦度特征;最后,结合融合特征和支持向量机(SVM)分类器来实现ADHD的自动识别。实验共采集了17位正常对照组儿童和37位ADHD患儿的语音样本。实验结果表明,所提算法能自动检测正常儿童和ADHD患儿,识别正确率为91.38%。The clinicians diagnose Attention Deficit/Hyperactivity Disorder(ADHD) mainly based on on their subjective assessment,which lacks objective criteria to assist. To solve this problem,an automatic detection algorithm for ADHD based on speech pause and flatness was proposed. Firstly,the Frequency band Difference Energy Entropy Product(FDEEP)parameter was used to automatically locate the segment with voice from the speech and extract the speech pause features. Then,Transform Average Amplitude Squared Difference(TAASD)parameter was presented to calculate the voice multi-frequency and extract the flatness features. Finally,fusion features and the Support Vector Machine(SVM)classifier were combined to realize the automatic recognition of ADHD. The speech samples of the experiment were collected from 17normal control children and 37 children with ADHD. Experimental results show that the proposed algorithm can effectively discriminate the normal children and children with ADHD,with an accuracy of 91. 38%.

关 键 词：注意缺陷与多动障碍 频带差能熵积 停顿度 变换平均幅度平方差 平坦度 

分 类 号：TP391.1[自动化与计算机技术—计算机应用技术]