Abstract
Vocabulary size has been suggested as a useful measure of “verbal abilities” that correlates with speech recognition scores. Knowing more words is linked to better speech recognition. How vocabulary knowledge translates to general speech recognition mechanisms, how these mechanisms relate to offline speech recognition scores, and how they may be modulated by acoustical distortion or age, is less clear. Age-related differences in linguistic measures may predict age-related differences in speech recognition in noise performance. We hypothesized that speech recognition performance can be predicted by the efficiency of lexical access, which refers to the speed with which a given word can be searched and accessed relative to the size of the mental lexicon. We tested speech recognition in a clinical German sentence-in-noise test at two signal-to-noise ratios (SNRs), in 22 younger (18–35 years) and 22 older (60–78 years) listeners with normal hearing. We also assessed receptive vocabulary, lexical access time, verbal working memory, and hearing thresholds as measures of individual differences. Age group, SNR level, vocabulary size, and lexical access time were significant predictors of individual speech recognition scores, but working memory and hearing threshold were not. Interestingly, longer accessing times were correlated with better speech recognition scores. Hierarchical regression models for each subset of age group and SNR showed very similar patterns: the combination of vocabulary size and lexical access time contributed most to speech recognition performance; only for the younger group at the better SNR (yielding about 85% correct speech recognition) did vocabulary size alone predict performance. Our data suggest that successful speech recognition in noise is mainly modulated by the efficiency of lexical access. This suggests that older adults’ poorer performance in the speech recognition task may have arisen from reduced efficiency in lexical access; with an average vocabulary size similar to that of younger adults, they were still slower in lexical access.
Highlights
Speech perception in background noise is relatively difficult compared to speech perception in quiet, and it most likely depends on a conglomerate of multiple factors (e.g., Benichov et al, 2012; Humes et al, 2012; Füllgrabe et al, 2015)
We determined which individual difference measures change with age, determined which of these measures explain variance of our speech in noise task, and tested whether age-related differences in the individual difference measures relate to the age-related differences for the speech recognition task
Our multivariate analysis of variance (MANOVA) suggested AGEGROUP effects in working memory and lexical access
Summary
Speech perception in background noise is relatively difficult compared to speech perception in quiet, and it most likely depends on a conglomerate of multiple factors (e.g., Benichov et al, 2012; Humes et al, 2012; Füllgrabe et al, 2015). Speech recognition is well-documented to deteriorate with decreasing SNR (Plomp and Mimpen, 1979; Kollmeier and Wesselkamp, 1997; Bruce et al, 2013). Cognitive factors such as (verbal) working memory, sensitivity to interference, attention, processing speed, or adaptive learning have been shown to contribute to speech perception in noise (Pichora-Fuller, 2003; Pichora-Fuller and Souza, 2003; Füllgrabe and Moore, 2014; Füllgrabe, 2015; Heinrich et al, 2015; Huettig and Janse, 2016). The umbrella term ‘individual difference measures’ refers to the collection of all of these measures
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