Predicting effects of spectral shaping on speech recognition of hearing-impaired listeners

The effects of spectral modification on speech recognition were investigated for sensorineural listeners: One group with flat audiometric configuration and a second group with sharply-sloping high-frequency hearing loss. Three spectral shapes were tested: Uniform frequency gain, high-pass filtering, and a response shaped relative to loudness discomfort levels. Performance-intensity functions were measured at four levels (from 80–95 dB SPL) using the CUNY Nonsense Syllable Test (NST) and the Synthetic Sentence Identification task (SSI), both presented monaurally under earphones against a background of multitalker babble. No significant differences in performance on the NST were observed between the two subject groups across all spectral shapes and presentation levels. On the SSI, performance of subjects with flat audiometric configuration was highest using the uniform frequency response, while performance of listeners with sloping hearing loss was poorest for the uniform spectral shape. The recognition data were compared with predictions of relative performance using a modification of the Articulation Index. The AI provided accurate estimates of relative performance across spectral shapes, but were not consistent with relative performance as a function of presentation level. [Work supported by NIH.]