Benefits of app-based speech in noise screener for children

Abstract

Current hearing screening methods focus on assessing a child’s ability to hear tones in quiet. However, this isn’t reflective of real-world classroom situations. Our proposed screening test uses speech in quiet and noise to evaluate a child’s auditory comprehension and possible auditory processing abilities. In this study, we investigate whether a speech in noise screener, Hearing Assessment in Response to Noise Screener (HeARS), is sensitive to detecting possible listening difficulties. We measured responses to a four-choice task with adapting signal to noise ratios based on individual performance. Following an auditory stimulus, the child is presented with four choices that are visual images of the spoken words. The child selects the correct image they hear, and based on their performance the signal to noise ratios increase or decrease in difficulty. Scores are reported as percent correct. We hypothesized that results from the screener would capture differences between speech understanding in noise and quiet conditions. In addition, a speech in noise screener may be more sensitive to deficits in auditory comprehension than traditional screening methods. Preliminary data suggest that the accuracy of understanding words in background noise increases with age. Results have implications for identifying children with auditory comprehension and processing deficits sooner, especially in underserved populations.