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青少年在家庭互动中的言语中临床抑郁的检测。

Detection of clinical depression in adolescents' speech during family interactions.

机构信息

School of Electrical and Computer Engineering, Royal Melbourne Institute of Technology, Vic. 3001, Australia.

出版信息

IEEE Trans Biomed Eng. 2011 Mar;58(3):574-86. doi: 10.1109/TBME.2010.2091640. Epub 2010 Nov 11.

Abstract

The properties of acoustic speech have previously been investigated as possible cues for depression in adults. However, these studies were restricted to small populations of patients and the speech recordings were made during patients' clinical interviews or fixed-text reading sessions. Symptoms of depression often first appear during adolescence at a time when the voice is changing, in both males and females, suggesting that specific studies of these phenomena in adolescent populations are warranted. This study investigated acoustic correlates of depression in a large sample of 139 adolescents (68 clinically depressed and 71 controls). Speech recordings were made during naturalistic interactions between adolescents and their parents. Prosodic, cepstral, spectral, and glottal features, as well as features derived from the Teager energy operator (TEO), were tested within a binary classification framework. Strong gender differences in classification accuracy were observed. The TEO-based features clearly outperformed all other features and feature combinations, providing classification accuracy ranging between 81%-87% for males and 72%-79% for females. Close, but slightly less accurate, results were obtained by combining glottal features with prosodic and spectral features (67%-69% for males and 70%-75% for females). These findings indicate the importance of nonlinear mechanisms associated with the glottal flow formation as cues for clinical depression.

摘要

先前已有研究调查了语音的声学特性是否可作为成人抑郁的线索。然而,这些研究仅限于小部分患者群体,且语音记录是在患者的临床访谈或固定文本阅读期间进行的。抑郁症状通常首先出现在青春期,此时男女的声音都在发生变化,这表明有必要对青少年群体中的这些现象进行专门研究。本研究在一个由 139 名青少年(68 名临床抑郁患者和 71 名对照者)组成的大样本中调查了抑郁的声学相关因素。在青少年与父母的自然互动期间进行了语音记录。在二元分类框架内测试了韵律、倒谱、频谱和声门特征,以及源自 Teager 能量算子(TEO)的特征。观察到分类准确性存在强烈的性别差异。基于 TEO 的特征明显优于所有其他特征和特征组合,为男性提供了 81%-87%的分类准确性,为女性提供了 72%-79%的分类准确性。将声门特征与韵律和频谱特征相结合可获得更接近但准确性略低的结果(男性为 67%-69%,女性为 70%-75%)。这些发现表明,与声门气流形成相关的非线性机制作为临床抑郁的线索非常重要。

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