Department of Linguistics, Cognitive Science and Semiotics, School of Communication and Culture, Aarhus University, Aarhus, Denmark.
Interacting Minds Center, School of Culture and Society, Aarhus University, Aarhus, Denmark.
Autism Res. 2022 Apr;15(4):653-664. doi: 10.1002/aur.2661. Epub 2021 Dec 26.
Acoustic atypicalities in speech production are argued to be potential markers of clinical features in autism spectrum disorder (ASD). A recent meta-analysis highlighted shortcomings in the field, in particular small sample sizes and study heterogeneity. We showcase a cumulative (i.e., explicitly building on previous studies both conceptually and statistically) yet self-correcting (i.e., critically assessing the impact of cumulative statistical techniques) approach to prosody in ASD to overcome these issues. We relied on the recommendations contained in the meta-analysis to build and analyze a cross-linguistic corpus of multiple speech productions in 77 autistic and 72 neurotypical children and adolescents (>1000 recordings in Danish and US English). We used meta-analytically informed and skeptical priors, with informed priors leading to more generalizable inference. We replicated findings of a minimal cross-linguistically reliable distinctive acoustic profile for ASD (higher pitch and longer pauses) with moderate effect sizes. We identified novel reliable differences between the two groups for normalized amplitude quotient, maxima dispersion quotient, and creakiness. However, the differences were small, and there is likely no one acoustic profile characterizing all autistic individuals. We identified reliable relations of acoustic features with individual differences (age, gender), and clinical features (speech rate and ADOS sub-scores). Besides cumulatively building our understanding of acoustic atypicalities in ASD, the study shows how to use systematic reviews and meta-analyses to guide the design and analysis of follow-up studies. We indicate future directions: larger and more diverse cross-linguistic datasets, focus on heterogeneity, self-critical cumulative approaches, and open science. LAY SUMMARY: Autistic individuals are reported to speak in distinctive ways. Distinctive vocal production can affect social interactions and social development and could represent a noninvasive way to support the assessment of autism spectrum disorder (ASD). We systematically checked whether acoustic atypicalities highlighted in previous articles could be actually found across multiple recordings and two languages. We find a minimal acoustic profile of ASD: higher pitch, longer pauses, increased hoarseness and creakiness of the voice. However, there is much individual variability (by age, sex, language, and clinical characteristics). This suggests that the search for one common "autistic voice" might be naive and more fine-grained approaches are needed.
言语产生中的声学异常被认为是自闭症谱系障碍(ASD)临床特征的潜在标志物。最近的一项荟萃分析强调了该领域的不足之处,特别是样本量小和研究异质性。我们展示了一种累积(即从概念和统计两个方面明确建立在前人研究的基础上)但自我修正(即批判性评估累积统计技术的影响)的方法来研究 ASD 中的韵律,以克服这些问题。我们依赖于荟萃分析中的建议,构建和分析了 77 名自闭症和 72 名神经典型儿童和青少年的多种言语产生的跨语言语料库(丹麦语和美式英语中有超过 1000 个录音)。我们使用了包含荟萃分析信息的、持怀疑态度的先验概率,有信息的先验概率导致更具普遍性的推断。我们复制了 ASD 中最小的跨语言可靠的独特声学特征(更高的音高和更长的停顿)的发现,具有中等的效应大小。我们确定了两组之间在归一化幅度商、最大值分散商和嘶哑度方面的新的可靠差异。然而,这些差异很小,而且可能没有一个声学特征可以描述所有自闭症个体。我们还确定了声学特征与个体差异(年龄、性别)和临床特征(言语速度和 ADOS 子分数)之间的可靠关系。除了累积地加深我们对 ASD 中声学异常的理解外,该研究还展示了如何使用系统评价和荟萃分析来指导后续研究的设计和分析。我们指出了未来的方向:更大和更多样化的跨语言数据集、关注异质性、自我批判性的累积方法和开放科学。