Prediction of individual speech recognition performance in complex listening conditions.

Abstract

This study examined how well individual speech recognition thresholds in complex listening scenarios could be predicted by a current binaural speech intelligibility model. Model predictions were compared with experimental data measured for seven normal-hearing and 23 hearing-impaired listeners who differed widely in their degree of hearing loss, age, as well as performance in clinical speech tests. The experimental conditions included two masker types (multi-talker or two-talker maskers), and two spatial conditions (maskers co-located with the frontal target or symmetrically separated from the target). The results showed that interindividual variability could not be well predicted by a model including only individual audiograms. Predictions improved when an additional individual "proficiency factor" was derived from one of the experimental conditions or a standard speech test. Overall, the current model can predict individual performance relatively well (except in conditions high in informational masking), but the inclusion of age-related factors may lead to even further improvements.