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Understanding speech in noise is particularly difficult for individuals occupationally exposed to noise due to a mix of noise-induced auditory lesions and the energetic masking of speech signals. For years, the monitoring of conventional audiometric thresholds has been the usual method to check and preserve auditory function. Recently, suprathreshold deficits, notably, difficulties in understanding speech in noise, has pointed out the need for new monitoring tools. The present study aims to identify the most important variables that predict speech in noise understanding in order to suggest a new method of hearing status monitoring. Physiological (distortion products of otoacoustic emissions, electrocochleography) and behavioral (amplitude and frequency modulation detection thresholds, conventional and extended high-frequency audiometric thresholds) variables were collected in a population of individuals presenting a relatively homogeneous occupational noise exposure. Those variables were used as predictors in a statistical model (random forest) to predict the scores of three different speech-in-noise tests and a self-report of speech-in-noise ability. The extended high-frequency threshold appears to be the best predictor and therefore an interesting candidate for a new way of monitoring noise-exposed professionals.

Hearing loss is a major public health problem. In 2050, it could affect 2.5 billion people. It has therefore become necessary to prevent and diagnose them as early and as widely as possible. However, the costs of clinical equipment dedicated to the functional exploration of hearing remain high and hamper their distribution, while the technologies used are relatively basic. For example, the gold-standard pure-tone audiometry (PTA) essentially consists of emitting pure sounds. In addition, clinical audiometers are generally limited to PTA or few audiological tests, while hearing loss induce multiple functional deficits. Here, we present the Aupiometer, a low-cost audiometer implemented on a modular open-source system based on Raspberry Pi, and which integrates the entire technical framework necessary to carry out audiological measurements. Several hearing tests are already implemented (e.g. PTA, speech audiometry, questionnaires), while the clinical validity of the Aupiometer was verified on a panel of participants (N = 16) for an automated test of standard and extended high-frequency PTA, from 0.125 to 16 kHz, in comparison with a clinical audiometer. For this comparison between the two devices and over this wide frequency range, the difference is evaluated as less than ±10 dB for a 90% confidence interval, of the same order of magnitude as on test-retest differences on a single device. The interest of this device also extends to academic research as it should encourage the prototyping of innovative hearing tests by the community, in order to better understand the diversity of hearing problems in the population.