Background: The measurement and monitoring of generalized anxiety disorder requires frequent interaction with psychiatrists or psychologists. Access to mental health professionals is often difficult because of high costs or insufficient availability. The ability to assess generalized anxiety disorder passively and at frequent intervals could be a useful complement to conventional treatment and help with relapse monitoring. Prior work suggests that higher anxiety levels are associated with features of human speech. As such, monitoring speech using personal smartphones or other wearable devices may be a means to achieve passive anxiety monitoring. Objective: This study aims to validate the association of previously suggested acoustic and linguistic features of speech with anxiety severity. Methods: A large number of participants (n=2000) were recruited and participated in a single web-based study session. Participants completed the Generalized Anxiety Disorder 7-item scale assessment and provided an impromptu speech sample in response to a modified version of the Trier Social Stress Test. Acoustic and linguistic speech features were a priori selected based on the existing speech and anxiety literature, along with related features. Associations between speech features and anxiety levels were assessed using age and personal income as covariates. Results: Word count and speaking duration were negatively correlated with anxiety scores (r=–0.12; P<.001), indicating that participants with higher anxiety scores spoke less. Several acoustic features were also significantly (P<.05) associated with anxiety, including the mel-frequency cepstral coefficients, linear prediction cepstral coefficients, shimmer, fundamental frequency, and first formant. In contrast to previous literature, second and third formant, jitter, and zero crossing rate for the z score of the power spectral density acoustic features were not significantly associated with anxiety. Linguistic features, including negative-emotion words, were also associated with anxiety (r=0.10; P<.001). In addition, some linguistic relationships were sex dependent. For example, the count of words related to power was positively associated with anxiety in women (r=0.07; P=.03), whereas it was negatively associated with anxiety in men (r=–0.09; P=.01). Conclusions: Both acoustic and linguistic speech measures are associated with anxiety scores. The amount of speech, acoustic quality of speech, and gender-specific linguistic characteristics of speech may be useful as part of a system to screen for anxiety, detect relapse, or monitor treatment.

中文翻译：

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即兴演讲的声学和语言特征及其与焦虑的关系：验证研究

背景：广泛性焦虑症的测量和监测需要经常与精神科医生或心理学家互动。由于成本高或可用性不足，通常很难接触到精神卫生专业人员。被动和频繁评估广泛性焦虑症的能力可能是对常规治疗的有用补充，并有助于监测复发。先前的工作表明，较高的焦虑水平与人类语言的特征有关。因此，使用个人智能手机或其他可穿戴设备监控语音可能是实现被动焦虑监控的一种手段。目的：本研究旨在验证先前提出的语音的声学和语言特征与焦虑严重程度之间的关联。方法：招募了大量参与者（n = 2000）并参加了一次基于网络的研究会议。参与者完成了广泛性焦虑症 7 项量表评估，并提供了一个即兴演讲样本，以响应修改版的特里尔社会压力测试。声学和语言语音特征是根据现有的语音和焦虑文献以及相关特征先验选择的。使用年龄和个人收入作为协变量来评估言语特征和焦虑水平之间的关联。结果：字数和说话时长与焦虑评分呈负相关（r =–0.12；P<.001），表明焦虑评分较高的参与者说话较少。几个声学特征也与焦虑显着相关（P <.05），包括梅尔频率倒谱系数、线性预测倒谱系数、微光、基频和第一共振峰。与以前的文献相比，功率谱密度声学特征的z分数的第二和第三共振峰、抖动和过零率与焦虑没有显着相关性。包括负面情绪词在内的语言特征也与焦虑有关（r = 0.10；P<.001)。此外，一些语言关系依赖于性别。例如，与权力相关的字数与女性的焦虑呈正相关（r =0.07；P =.03），而与男性的焦虑呈负相关（r =–0.09；P =.01）。结论：声学和语言言语测量都与焦虑评分相关。语音的数量、语音的声学质量和语音的性别特定语言特征可能作为系统的一部分用于筛查焦虑、检测复发或监测治疗。