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. 2017 May;56(5):306-315.
doi: 10.1080/14992027.2016.1266703. Epub 2016 Dec 16.

Individual differences in language and working memory affect children's speech recognition in noise

Ryan W McCreery  1 , Meredith Spratford  1 , Benjamin Kirby  2 , Marc Brennan  1
Affiliations

Individual differences in language and working memory affect children's speech recognition in noise

Ryan W McCreery et al. Int J Audiol. 2017 May.

Abstract

Objective: We examined how cognitive and linguistic skills affect speech recognition in noise for children with normal hearing. Children with better working memory and language abilities were expected to have better speech recognition in noise than peers with poorer skills in these domains.

Design: As part of a prospective, cross-sectional study, children with normal hearing completed speech recognition in noise for three types of stimuli: (1) monosyllabic words, (2) syntactically correct but semantically anomalous sentences and (3) semantically and syntactically anomalous word sequences. Measures of vocabulary, syntax and working memory were used to predict individual differences in speech recognition in noise.

Study sample: Ninety-six children with normal hearing, who were between 5 and 12 years of age.

Results: Higher working memory was associated with better speech recognition in noise for all three stimulus types. Higher vocabulary abilities were associated with better recognition in noise for sentences and word sequences, but not for words.

Conclusions: Working memory and language both influence children's speech recognition in noise, but the relationships vary across types of stimuli. These findings suggest that clinical assessment of speech recognition is likely to reflect underlying cognitive and linguistic abilities, in addition to a child's auditory skills, consistent with the Ease of Language Understanding model.

Keywords: Behavioural measures; noise; paediatric; psychoacoustics/hearing science; speech perception.

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Conflict of interest statement

Declaration of interest: The authors report no conflicts of interest. The authors alone are responsible for the content and writing of this article. This work was supported by grants from NIH-NIDCD (R03 DC012635, R01 DC013591, P30 DC004662, T32 DC000013).

Figures

Figure 1
Figure 1
Box plots of the standard scores for language and cognitive measures for children who participated in the study. The boxes represent the interquartile range (25th–75th percentiles) and the whiskers represent the range of the 5th and 95th percentiles. The horizontal lines within each bar represent the medians and the filled circles represent the mean. The hatched area represents 1 standard deviation from the normative mean for each measure. PPVT =Peabody Picture Vocabulary Test; TROG =Test of Reception of Grammar; Nonword =Automated Working Memory Assessment (AWMA) Nonword Recall Subtest; Dot =AWMA Dot Matrix Subtest; Counting =AWMA Counting Recall Subtest; Odd =AWMA Odd-one-out subtest.
Figure 2
Figure 2
Box plots of the signal-to-noise ratios (SNRs) for 71% (dark grey) and 29% (light grey) for words, low predictability (LP) sentences and zero-predictability (ZP) sequences. The boxes represent the interquartile range (25th–75th percentiles) and the whiskers represent the range of the 5th and 95th percentiles. The horizontal lines within each bar represent the medians and the filled circles represent the means. The stars represent data points that were outside of the range for the 5th–95th percentiles.
See this image and copyright information in PMC

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