The Bilingual Disadvantage in Speech Understanding in Noise Is Likely a Frequency Effect Related to Reduced Language Exposure

The present study sought to explain why bilingual speakers are disadvantaged relative to monolingual speakers when it comes to speech understanding in noise. Exemplar models of the mental lexicon hold that each encounter with a word leaves a memory trace in long-term memory. Words that we encounter frequently will be associated with richer phonetic representations in memory and therefore recognized faster and more accurately than less frequently encountered words. Because bilinguals are exposed to each of their languages less often than monolinguals by virtue of speaking two languages, they encounter all words less frequently and may therefore have poorer phonetic representations of all words compared to monolinguals. In the present study, vocabulary size was taken as an estimate for language exposure and the prediction was made that both vocabulary size and word frequency would be associated with recognition accuracy for words presented in noise. Forty-eight early Spanish–English bilingual and 53 monolingual English young adults were tested on speech understanding in noise (SUN) ability, English oral verbal ability, verbal working memory (WM), and auditory attention. Results showed that, as a group, monolinguals recognized significantly more words than bilinguals. However, this effect was attenuated by language proficiency; higher proficiency was associated with higher accuracy on the SUN test in both groups. This suggests that greater language exposure is associated with better SUN. Word frequency modulated recognition accuracy and the difference between groups was largest for low frequency words, suggesting that the bilinguals’ insufficient exposure to these words hampered recognition. The effect of WM was not significant, likely because of its large shared variance with language proficiency. The effect of auditory attention was small but significant. These results are discussed within the Ease of Language Understanding model (Rönnberg et al., 2013), which provides a framework for explaining individual differences in SUN.