The detection of changes in mental states such as those caused by psychoactive drugs relies on clinical assessments that are inherently subjective. Automated speech analysis may represent a novel method to detect objective markers, which could help improve the characterization of these mental states. In this study, we employed computer-extracted speech features from multiple domains (acoustic, semantic, and psycholinguistic) to assess mental states after controlled administration of 3,4-methylenedioxymethamphetamine (MDMA) and intranasal oxytocin. The training/validation set comprised within-participants data from 31 healthy adults who, over four sessions, were administered MDMA (0.75, 1.5 mg/kg), oxytocin (20 IU), and placebo in randomized, double-blind fashion. Participants completed two 5-min speech tasks during peak drug effects. Analyses included group-level comparisons of drug conditions and estimation of classification at the individual level within this dataset and on two independent datasets. Promising classification results were obtained to detect drug conditions, achieving cross-validated accuracies of up to 87% in training/validation and 92% in the independent datasets, suggesting that the detected patterns of speech variability are associated with drug consumption. Specifically, we found that oxytocin seems to be mostly driven by changes in emotion and prosody, which are mainly captured by acoustic features. In contrast, mental states driven by MDMA consumption appear to manifest in multiple domains of speech. Furthermore, we find that the experimental task has an effect on the speech response within these mental states, which can be attributed to presence or absence of an interaction with another individual. These results represent a proof-of-concept application of the potential of speech to provide an objective measurement of mental states elicited during intoxication.

中文翻译：

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使用自动自然语言处理检测跨协议的急性 3,4-亚甲二氧基甲基苯丙胺 (MDMA) 效应。

检测精神状态的变化（例如由精神活性药物引起的变化）依赖于本质上是主观的临床评估。自动语音分析可能是一种检测客观标记的新方法，有助于改善对这些心理状态的表征。在这项研究中，我们采用了从多个领域（声学、语义和心理语言学）中计算机提取的语音特征来评估受控施用 3,4-亚甲二氧基甲基苯丙胺 (MDMA) 和鼻内催产素后的心理状态。训练/验证集包括来自 31 名健康成年人的参与者内部数据，他们在四次会议中以随机、双盲方式服用 MDMA（0.75、1.5 毫克/千克）、催产素（20 IU）和安慰剂。参与者在药物作用高峰期间完成了两次 5 分钟的演讲任务。分析包括在该数据集内和两个独立数据集上的药物状况的组级比较和个体级别的分类估计。获得了有希望的分类结果来检测药物状况，在训练/验证中实现了高达 87% 的交叉验证准确度，在独立数据集中实现了 92%，这表明检测到的语音变异模式与药物消耗有关。具体来说，我们发现催产素似乎主要由情绪和韵律的变化驱动，这些变化主要由声学特征捕获。相比之下，由 MDMA 消费驱动的精神状态似乎表现在多个语音领域。此外，我们发现实验任务对这些心理状态下的言语反应有影响，这可以归因于与另一个人互动的存在或不存在。这些结果代表了语音潜力的概念验证应用，可提供对醉酒期间引起的心理状态的客观测量。