The stability and validity of automated vocal analysis in preverbal preschoolers with autism spectrum disorder.
The stability and validity of automated vocal analysis in preverbal preschoolers with autism spectrum disorder.
复制标题
患有自闭症谱系障碍的学龄前儿童自动声音分析的稳定性和有效性。
DOI：
10.1002/aur.1667
复制
发表时间：
2017
期刊：
影响因子：
--
通讯作者：
Yoder,Paul
中科院分区：
文献类型：
--
作者：
Woynaroski,Tiffany;Oller,DKimbrough;Keceli-Kaysili,Bahar;Xu,Dongxin;Richards,JeffreyA;Gilkerson,Jill;Gray,Sharmistha;Yoder,Paul
理论和研究表明，在患有自闭症谱系障碍（ASD）的学龄前儿童中，声音发育预示着“有用的语言”，但传统的测量声音发育的方法既昂贵又耗时。本纵向相关研究考察了几个发声发展的自动指标相对于一个来自人类编码的、传统的ASD学龄前儿童语言前交流样本的指标的可靠性和有效性。语音发展的自动指标是使用目前“正在开发”和/或仅用于研究目的的软件和使用商业上可用的语言环境分析（LENA）软件得出的。使用可用于研究目的的软件得出的语音发展指数：(a)在一天的录音中高度稳定，(b)预测未来口语词汇量的程度与传统交流样本得出的指数没有显著差异，(c)即使在控制了样本中的并发词汇量之后，仍能预测未来口语词汇量。由标准LENA软件得出的分数同样稳定，但与未来的口语词汇量没有显著相关。研究结果表明，在研究和临床实践中，自动化语音分析是一种有效和可靠的方法，可以替代耗时且昂贵的传统交流样本来测量ASD学龄前儿童的语音发展。孤独症杂志，2017,(10):508-519。©2016国际自闭症研究协会，Wiley期刊公司。
Theory and research suggest that vocal development predicts “useful speech” in preschoolers with autism spectrum disorder (ASD), but conventional methods for measurement of vocal development are costly and time consuming. This longitudinal correlational study examines the reliability and validity of several automated indices of vocalization development relative to an index derived from human coded, conventional communication samples in a sample of preverbal preschoolers with ASD. Automated indices of vocal development were derived using software that is presently “in development” and/or only available for research purposes and using commercially available Language ENvironment Analysis (LENA) software. Indices of vocal development that could be derived using the software available for research purposes: (a) were highly stable with a single day‐long audio recording, (b) predicted future spoken vocabulary to a degree that was nonsignificantly different from the index derived from conventional communication samples, and (c) continued to predict future spoken vocabulary even after controlling for concurrent vocabulary in our sample. The score derived from standard LENA software was similarly stable, but was not significantly correlated with future spoken vocabulary. Findings suggest that automated vocal analysis is a valid and reliable alternative to time intensive and expensive conventional communication samples for measurement of vocal development of preverbal preschoolers with ASD in research and clinical practice.Autism Res2017, 10: 508–519. © 2016 International Society for Autism Research, Wiley Periodicals, Inc.
登录
查看更多内容
自动语音教练为家长提供对话提示
影响因子：
1.7
作者：
H. Hodson
通讯作者：
H. Hodson
影响因子：
7
作者：
L. Collins;J. Schafer;Chi-Ming Kam
通讯作者：
L. Collins;J. Schafer;Chi-Ming Kam
18 个月大时的联合注意状态和词汇习得。
影响因子：
4
作者：
P. Dunham;F. Dunham;A. Curwin
通讯作者：
A. Curwin
影响因子：
3.9
作者：
Sheinkopf, SJ;Mundy, P;Steffens, M
通讯作者：
Steffens, M
影响因子：
2.7
作者：
Reeve,L;Reeve,KF;Brown,AK;Brown,JL;Poulson,CL
通讯作者：
Poulson,CL