How effective is LENA in detecting speech vocalizations and language produced by children and adolescents with ASD in different contexts?
How effective is LENA in detecting speech vocalizations and language produced by children and adolescents with ASD in different contexts?
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LENA 在检测自闭症儿童和青少年在不同环境中发出的言语和语言方面的效果如何？
DOI：
10.1002/aur.2071
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发表时间：
2019
期刊：
影响因子：
--
通讯作者：
Tager-Flusberg,Helen
中科院分区：
文献类型：
--
作者：
Jones,RebeccaM;PlesaSkwerer,Daniela;Pawar,Rahul;Hamo,Amarelle;Carberry,Caroline;Ajodan,ElianaL;Caulley,Desmond;Silverman,MelanieR;McAdoo,Shannon;Meyer,Steven;Yoder,Anne;Clements,Mark;Lord,Catherine;Tager-Flusberg,Helen
LENA 系统的设计和验证旨在提供有关 0 至 4 岁儿童语言环境的信息，其用途已扩展到具有多种沟通模式的人群。它对于 5 岁及以上儿童的效用尚不清楚。本研究使用来自自闭症谱系障碍 (ASD) 儿童的两个样本的声学数据来评估 LENA 自动分析在诊所和家庭环境中检测患有 ASD 的较大学龄儿童和青少年言语的可靠性。年龄在 5 至 18 岁之间、语言水平最低（研究 1）或具有一定范围语言能力（研究 2）的参与者在诊所（研究 1 和 2）和家中（研究 2）完成标准化评估，同时通过 LENA 设备记录语音。我们使用两种不同的方法将 LENA 片段标签与人类转录员的手动地面实况编码进行了比较。我们发现，自动化 LENA 算法在检测患有自闭症谱系障碍 (ASD) 的较大儿童和青少年的发声方面并不成功（<50% 可靠），并且自动化系统对说话人进行错误分类的比例随着目标儿童年龄的增长而显着增加。对患有自闭症谱系障碍 (ASD) 的儿童和青少年的研究结果表明，将 LENA 的使用范围扩大到超出其开发年龄范围时可能会产生误导性结果，并强调需要开发更适合年龄较大儿童的新型自动化方法。 Autism Research2019, 12: 628–635。 © 2019 国际自闭症研究协会，Wiley periodicals, Inc.Lay 摘要当前商用语音检测算法（LENA 系统）之前已在幼儿和 48 个月以下的儿童中进行了验证，目前尚不清楚它们在年龄较大的儿童和青少年中是否可靠。我们的数据表明，LENA 未能充分捕捉学龄儿童和自闭症青少年的言语，并强调需要为年龄较大的儿童开发新的自动化方法。
The LENA system was designed and validated to provide information about the language environment in children 0 to 4 years of age and its use has been expanded to populations with a number of communication profiles. Its utility in children 5 years of age and older is not yet known. The present study used acoustic data from two samples of children with autism spectrum disorders (ASD) to evaluate the reliability of LENA automated analyses for detecting speech utterances in older, school age children, and adolescents with ASD, in clinic and home environments. Participants between 5 and 18 years old who were minimally verbal (study 1) or had a range of verbal abilities (study 2) completed standardized assessments in the clinic (study 1 and 2) and in the home (study 2) while speech was recorded from a LENA device. We compared LENA segment labels with manual ground truth coding by human transcribers using two different methods. We found that the automated LENA algorithms were not successful (<50% reliable) in detecting vocalizations from older children and adolescents with ASD, and that the proportion of speaker misclassifications by the automated system increased significantly with the target‐child's age. The findings in children and adolescents with ASD suggest possibly misleading results when expanding the use of LENA beyond the age ranges for which it was developed and highlight the need to develop novel automated methods that are more appropriate for older children.Autism Research2019, 12: 628–635. © 2019 International Society for Autism Research, Wiley Periodicals, Inc.Lay SummaryCurrent commercially available speech detection algorithms (LENA system) were previously validated in toddlers and children up to 48 months of age, and it is not known whether they are reliable in older children and adolescents. Our data suggest that LENA does not adequately capture speech in school age children and adolescents with autism and highlights the need to develop new automated methods for older children.
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影响因子：
3.7
作者：
Ramírez-Esparza N;García-Sierra A;Kuhl PK
通讯作者：
Kuhl PK
影响因子：
3.9
作者：
Sheinkopf, SJ;Mundy, P;Steffens, M
通讯作者：
Steffens, M
自闭症谱系障碍的语法语言障碍：探索标准化测试之外的语言表型
影响因子：
3.8
作者：
Kacie Wittke;Ann M. Mastergeorge;S. Ozonoff;S. Rogers;Letitia R. Naigles
通讯作者：
Letitia R. Naigles
DOI：
--
发表时间：
1987
期刊：
影响因子：
--
作者：
G. McCloskey
通讯作者：
G. McCloskey
DOI：
10.1016/bs.irrdd.2016.05.006
发表时间：
2016-01-01
期刊：
FIFTY YEARS OF RESEARCH IN INTELLECTUAL AND DEVELOPMENTAL DISABILITIES
影响因子：
--
作者：
Abbeduto, L.;McDuffie, A.;Kover, S. T.
通讯作者：
Kover, S. T.