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选择一种声学相关特征用于自动测量儿童美式英语中r音的发音情况。

Selecting an acoustic correlate for automated measurement of American English rhotic production in children.

作者信息

Campbell Heather, Harel Daphna, Hitchcock Elaine, McAllister Byun Tara

机构信息

a Department of Communicative Sciences and Disorders, NYU Steinhardt School of Culture , Education, & Human Development , New York , NY , USA.

b Center for the Promotion of Research Involving Innovative Statistical Methodology , New York , NY , USA , and.

出版信息

Int J Speech Lang Pathol. 2018 Nov;20(6):635-643. doi: 10.1080/17549507.2017.1359334. Epub 2017 Aug 10.

Abstract

: A current need in the field of speech-language pathology is the development of reliable and efficient techniques to evaluate accuracy of speech targets over the course of treatment. As acoustic measurement techniques improve, it should become possible to use automated scoring in lieu of ratings from a trained clinician in some contexts. This study asks which acoustic measures correspond most closely with expert ratings of children's productions of American English /ɹ/ in an effort to develop an automated scoring algorithm for use in treatment targeting rhotics. : A series of ordinal mixed-effects regression models were fit over a large sample of children's productions of words containing /ɹ/ that had previously been rated by three trained clinicians. Akaike/Bayesian Information Criteria were used to select the best-fitting model. : Controlling for age, sex, and allophonic contextual differences, the measure that accounted for the most variance in speech rating was F3-F2 distance normalised relative to a sample of age- and sex-matched speakers. : We recommend this acoustic measure for use in future automated scoring of children's production of American English rhotics. We also suggest that computer-based treatment with automated scoring should facilitate increases in treatment dosage by improving options for home practice.

摘要

言语病理学领域当前的一个需求是开发可靠且高效的技术,以在治疗过程中评估言语目标的准确性。随着声学测量技术的改进,在某些情况下,使用自动评分代替训练有素的临床医生的评分应该成为可能。本研究旨在探究哪些声学指标与专家对儿童美式英语/ɹ/发音的评分最为接近,以便开发一种用于针对卷舌音治疗的自动评分算法。:对大量包含/ɹ/的儿童单词发音样本拟合了一系列有序混合效应回归模型,这些样本此前已由三位训练有素的临床医生进行了评分。使用赤池/贝叶斯信息准则来选择最佳拟合模型。:在控制年龄、性别和音位语境差异的情况下,在言语评分中解释方差最多的指标是相对于年龄和性别匹配的说话者样本进行归一化的F3 - F2距离。:我们建议将此声学指标用于未来对儿童美式英语卷舌音发音的自动评分。我们还建议,基于计算机的自动评分治疗应通过改善家庭练习选项来促进治疗剂量的增加。

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