Purpose The aim of this study was to develop and evaluate a novel, automated speech-in-noise test viable for widespread in situ and remote screening. Method Vowel–consonant–vowel sounds in a multiple-choice consonant discrimination task were used. Recordings from a professional male native English speaker were used. A novel adaptive staircase procedure was developed, based on the estimated intelligibility of stimuli rather than on theoretical binomial models. Test performance was assessed in a population of 26 young adults (YAs) with normal hearing and in 72 unscreened adults (UAs), including native and nonnative English listeners. Results The proposed test provided accurate estimates of the speech recognition threshold (SRT) compared to a conventional adaptive procedure. Consistent outcomes were observed in YAs in test/retest and in controlled/uncontrolled conditions and in UAs in native and nonnative listeners. The SRT increased with increasing age, hearing loss, and self-reported hearing handicap in UAs. Test duration was similar in YAs and UAs irrespective of age and hearing loss. The test–retest repeatability of SRTs was high (Pearson correlation coefficient = .84), and the pass/fail outcomes of the test were reliable in repeated measures (Cohen's κ = .8). The test was accurate in identifying ears with pure-tone thresholds > 25 dB HL (accuracy = 0.82). Conclusion This study demonstrated the viability of the proposed test in subjects of varying language in terms of accuracy, reliability, and short test time. Further research is needed to validate the test in a larger population across a wider range of languages and hearing loss and to identify optimal classification criteria for screening purposes.

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This article presents a preliminary evaluation of a novel language independent Speech-in-Noise test for adult screening in terms of Speech Reception Threshold (SRT) estimates and prediction of hearing sensitivity. The test is based on multiple-choice recognition of meaningless Vowel-Consonant-Vowel words and was administered to 26 normal hearing young adults and 58 unscreened adults who also underwent pure-tone audiometry. Receiver operating characteristics were built using the World Health Organization criteria for "slight/mild" and "moderate" hearing loss as gold standards and SRTs as test outcome. Both curves showed very good test performance in predicting success/failure in pure-tone audiometry (area under the curve: 0.79 for "slight/mild" and 0.83 for "moderate" hearing loss). A complete generalized linear model including SRT, age, and their interaction showed that the SRT and the interaction between SRT and age were significant predictors of pure-tone audiometry outcomes, whereas age alone was not a significant predictor of the degree of hearing loss. Moreover, preliminary results from test-retest data showed that the test was reliable in repeated measures (Spearman's rank-order correlation coefficient = 0.72; Cohen's kappa = 0.83 for "slight/mild" and 0.64 for "moderate" hearing loss). Further research is needed to fully assess test performance in a larger sample of participants, also including subjects with higher degrees of hearing loss (e.g. "severe" and "profound").

One of the current gaps in teleaudiology is the lack of methods for adult hearing screening viable for use in individuals of unknown language and in varying environments. We have developed a novel automated speech-in-noise test that uses stimuli viable for use in non-native listeners. The test reliability has been demonstrated in laboratory settings and in uncontrolled environmental noise settings in previous studies. The aim of this study was: (i) to evaluate the ability of the test to identify hearing loss using multivariate logistic regression classifiers in a population of 148 unscreened adults and (ii) to evaluate the ear-level sound pressure levels generated by different earphones and headphones as a function of the test volume. The multivariate classifiers had sensitivity equal to 0.79 and specificity equal to 0.79 using both the full set of features extracted from the test as well as a subset of three features (speech recognition threshold, age, and number of correct responses). The analysis of the ear-level sound pressure levels showed substantial variability across transducer types and models, with earphones levels being up to 22 dB lower than those of headphones. Overall, these results suggest that the proposed approach might be viable for hearing screening in varying environments if an option to self-adjust the test volume is included and if headphones are used. Future research is needed to assess the viability of the test for screening at a distance, for example by addressing the influence of user interface, device, and settings, on a large sample of subjects with varying hearing loss.