Language-Independent Hearing Screening Based on Masked Recognition of Ecological Sounds

Abstract

A language-independent automated self-test on tablet based on masked recognition of ecological sounds, the Sound Ear Check (SEC), was developed. In this test, 24 trials of eight different sounds are randomly presented in a noise that was spectrally shaped according to the average frequency spectra of the stimulus sounds, using a 1-up 2-down adaptive procedure. The test was evaluated in adults with normal hearing and hearing loss, and its feasibility was investigated in young children, who are the target population of this test. Following equalization of perceptual difficulty across sounds by applying level adjustments to the individual tokens, a reference curve with a steep slope of 18%/dB was obtained, resulting in a test with a high test–retest reliability of 1 dB. The SEC sound reception threshold was significantly associated with the averaged pure tone threshold ( r = .70), as well as with the speech reception threshold for the Digit Triplet Test ( r = .79), indicating that the SEC is susceptible to both audibility and signal-to-noise ratio loss. Sensitivity and specificity values on the order of magnitude of ∼70% and ∼80% to detect individuals with mild and moderate hearing loss, respectively, and ∼80% to detect individuals with slight speech-in-noise recognition difficulties were obtained. Homogeneity among sounds was verified in children. Psychometric functions fitted to the data indicated a steep slope of 16%/dB, and test–retest reliability of sound reception threshold estimates was 1.3 dB. A reference value of −9 dB signal-to-noise ratio was obtained. Test duration was around 6 minutes, including training and acclimatization.