The Contribution of Individual Differences in Memory Span and Language Ability to Spatial Release From Masking in Young Children

Abstract

Purpose Working memory capacity and language ability modulate speech reception; however, the respective roles of peripheral and cognitive processing are unclear. The contribution of individual differences in these abilities to utilization of spatial cues when separating speech from informational and energetic masking backgrounds in children has not yet been determined. Therefore, this study explored whether speech reception in children is modulated by environmental factors, such as the type of background noise and spatial configuration of target and noise sources, and individual differences in the cognitive and linguistic abilities of listeners. Method Speech reception thresholds were assessed in 39 children aged 5–7 years in simulated school listening environments. Speech reception thresholds of target sentences spoken by an adult male consisting of number and color combinations were measured using an adaptive procedure, with speech-shaped white noise and single-talker backgrounds that were either collocated (target and back-ground at 0°) or spatially separated (target at 0°, background noise at 90° to the right). Spatial release from masking was assessed alongside memory span and expressive language. Results and Conclusion Significant main effect results showed that speech reception thresholds were highest for informational maskers and collocated conditions. Significant interactions indicated that individual differences in memory span and language ability were related to spatial release from masking advantages. Specifically, individual differences in memory span and language were related to the utilization of spatial cues in separated conditions. Language differences were related to auditory stream segregation abilities in collocated conditions that lack helpful spatial cues, pointing to the utilization of language processes to make up for losses in spatial information.

Auditory, Cognitive, and Linguistic Factors Predict Speech Recognition in Adverse Listening Conditions for Children With Hearing Loss

“…The Ease of Language Understanding model (ELU; Rönnberg et al, 2013) is a model of language processing that suggests that listeners rely on their knowledge of language and cognitive skills like working memory and attention to understand speech in degraded conditions. The predictions of the ELU model that children with greater working memory capacities have better speech in noise than peers with reduced working memory capacities have been confirmed by some previous studies of speech recognition in noise for children with normal hearing (Stiles et al, 2012; Sullivan et al, 2015; McCreery et al, 2017; MacCutcheon et al, 2019). However, work by Magimairaj et al (2018) did not find an association between language or working memory and sentence recognition in babble noise for children with normal hearing.…”

“…The ability to understand degraded speech is an important developmental skill that does not reach full maturity until adolescence in children with typical hearing (Johnson, 2000; Corbin et al, 2016). The protracted developmental time course for speech recognition in adverse listening conditions in typically developing children has been attributed to the parallel maturation of cognitive and linguistic skills (Sullivan et al, 2015; McCreery et al, 2017; MacCutcheon et al, 2019).…”

Investigating the Effect of One Year of Learning to Play a Musical Instrument on Speech-in-Noise Perception and Phonological Short-Term Memory in 5-to-7-Year-Old Children

“…Binaural room impulse responses were simulated based on a head-related transfer function measured from a child dummy head so that the virtually simulated environment was appropriate for the sample under investigation (Fels et al, 2004). Further details about the masker and the simulation of the virtual acoustic environment are reported in MacCutcheon et al (2019). Speech identification was assessed using an adaptation of the "Children's Coordinate Response Measure" software described in Vickers et al (2016).…”

“…Classroom noise is known to cause distraction and annoyance in children, but its primary effect is a reduction in speech intelligibility (for reviews, see Shield and Dockrell, 2003;Klatte et al, 2013), with a consequently negative impact on academic achievement (Shield and Dockrell, 2008). In typically developing children, the ability to cope with speech in noise (SiN) has been linked to individual differences in cognitive and language abilities (Nelson et al, 2005;Strait et al, 2012;MacCutcheon et al, 2019), age (Corbin et al, 2016), gender (Prodi et al, 2019), and supra-threshold auditory processing abilities (Lorenzi et al, 2000), as well as environmental factors, including reverberation and the spatial, spectral and temporal characteristics of the background noise (MacCutcheon et al, 2018(MacCutcheon et al, , 2019McCreery et al, 2019).…”

“…Noise presents a challenge for speech perception as a consequence of the acoustic and spatial characteristics of the masker. Energetic maskers reduce speech intelligibility, while informational maskers reduce speech perception due to acoustic similarity with the target speech, resulting in perceptual confusion (Brungart, 2001;Wightman and Kistler, 2005;Wightman et al, 2006;MacCutcheon et al, 2019), and informational interference (Dole et al, 2012;Stone et al, 2012). Meanwhile, localization cues provided by the spatial separation of the target speech from the masker can improve intelligibility because timing and level differences between the two ears assist with sound segregation (Litovsky, 2005;Johnstone and Litovsky, 2006); referred to as "spatial release from masking" (Freyman et al, 1999;Hawley et al, 2004).…”