Ieee Transactions on Affective Computing 1 Detecting Depression Severity from Vocal Prosody
Ieee Transactions on Affective Computing 1 Detecting Depression Severity from Vocal Prosody
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通讯作者：
Ying Yang;Catherine Fairbairn;J. Cohn
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作者：
Ying Yang;Catherine Fairbairn;J. Cohn
--为了研究声音韵律与抑郁症严重程度随时间变化的关系，一项治疗抑郁症的临床试验的57名参与者每隔7周使用半结构化的抑郁症严重程度临床访谈(哈密尔顿抑郁症评价表：HRSD)进行评估。所有受试者在第一周都达到了严重抑郁障碍的标准。使用天真的听者的知觉判断和对发声时机和基频的定量分析，检验了三个假设：1)天真的听者可以从抑郁的参与者和面试者的声音记录中感知抑郁的严重程度。2)抑郁受试者的声韵定量特征揭示了抑郁过程中症状严重程度的变化。3)人际关系也会产生影响，面试官的语音韵律也会产生相应的影响。这些假设得到了强有力的支持。受试者和采访者的声音韵律共同解释了抑郁评分变化的60%，并在69%的病例中检测到抑郁严重程度的顺序范围(轻度、轻度和中重度)(kappa=0.53)。这些发现表明，对声音韵律的分析可能是一种强大的工具，有助于在抑郁障碍和康复过程中进行抑郁筛查和监测。
—To investigate the relation between vocal prosody and change in depression severity over time, 57 participants from a clinical trial for treatment of depression were evaluated at seven-week intervals using a semi-structured clinical interview for depression severity (Hamilton Rating Scale for Depression: HRSD). All participants met criteria for Major Depressive Disorder at week 1. Using both perceptual judgments by naive listeners and quantitative analyses of vocal timing and fundamental frequency, three hypotheses were tested: 1) Naive listeners can perceive the severity of depression from vocal recordings of depressed participants and interviewers. 2) Quantitative features of vocal prosody in depressed participants reveal change in symptom severity over the course of depression. And 3) Interpersonal effects occur as well; such that vocal prosody in interviewers shows corresponding effects. These hypotheses were strongly supported. Together, participants' and interviewers' vocal prosody accounted for about 60% of variation in depression scores, and detected ordinal range of depression severity (low, mild, and moderate-to-severe) in 69% of cases (kappa = 0.53). These findings suggest that analysis of vocal prosody could be a powerful tool to assist in depression screening and monitoring over the course of depressive disorder and recovery.