Early Detection of Autism through Acoustic Analysis of Cry

描述(由申请人提供)：初步证据表明，患有自闭症谱系障碍(ASD)的儿童在婴儿早期可能具有非典型哭闹的特征。此前的研究已经发现，患有自闭症的年龄较大的儿童在说话和发声的韵律质量方面存在非典型性，婴儿哭声的异常声学特征与儿童早期的发现是一致的。我们的实验室已经在一些临床人群中进行了哭声研究，包括(最近)后来被诊断为ASD的婴儿。我们实验室使用的哭声分析系统是专门针对婴儿发育中的声道进行模拟的。然而，目前的声学分析系统，包括我们自己的系统，可能不足以检测到这些非典型现象，特别是在它们可能很细微的地方。该项目将具有婴儿哭声产生和婴幼儿自闭症专业知识的研究人员以及在声学分析和语音识别工具开发方面具有丰富经验的实验室组成。该团队将合作开发一种新的基于最先进的声学工程和计算机技术的婴儿哭声分析系统。特别是，我们将利用数字信号处理的进步来产生更准确和健壮的婴儿哭声检测和建模。然后，我们将通过使用已经收集的大型哭声数据库，包括后来被诊断为自闭症谱系障碍的婴儿的哭声，来验证这个新系统与我们目前的系统的有效性。该项目可能导致一种简单的、非侵入性的程序，可以在出生后不久识别自闭症的迹象，并将具有巨大的公共卫生意义。 公共卫生相关性：这项研究对自闭症儿童的早期识别和干预都具有高度相关性。通过开发一种系统，可以识别与这种疾病相关的婴儿哭声的非典型方面，这项研究将有助于开发更敏感和具体的筛查和诊断工具，供婴儿使用。此外，这项研究将提高我们对自闭症沟通障碍的根源和过程的理解。

DESCRIPTION (provided by applicant): Preliminary evidence suggests that children with Autism Spectrum Disorders (ASD) may be characterized by atypical features of cry during early infancy. Previous research has identified atypicalities in prosodic qualities of speech and vocalizations in older children with autism, and unusual acoustic features of infant cry would be consistent with such findings from early childhood. Our lab has conducted studies of cry acoustics in a number of clinical populations, including (most recently) infants later diagnosed with an ASD. The cry analysis system utilized in our lab is specifically modeled on the infant's developing vocal tract. However, current acoustic analysis systems, including our own, may not be accurate enough to detect these atypicalities, especially where they may be subtle. This project teams researchers with expertise in infant cry production and autism in infancy and early childhood, as well as a lab with extensive experience in the development of acoustic analysis and speech recognition tools. This team will work collaboratively to develop a new acoustic analysis system for infant cry based on state of the art acoustical engineering and computer technology. In particular, we will utilize advances in digital signal processing to yield more accurate and robust detection and modeling of infant cry acoustics. We will then validate this new system against our current system by using a large data bank of cries already collected, including cries of infants who were later diagnosed with autism spectrum disorder. This project could lead to a simple, non-invasive procedure that could identify signs of autism shortly after birth and would have enormous public health significance. PUBLIC HEALTH RELEVANCE: This research is highly relevant to both early identification and intervention for children with autism. By developing a system that can identify atypical aspects of cry in infancy associated with this disorder, this research will aide in the development of more sensitive and specific screening and diagnostic tools for use in infancy. In addition, this research will improve our understanding of the roots and course of communication impairments in autism.