Maximizing Audibility and Speech Recognition With Nonlinear Frequency Compression by Estimating Audible Bandwidth

Objective: Nonlinear frequency compression attempts to restore high-frequency audibility by lowering high-frequency input signals. Methods of determining the optimal parameters that maximize speech understanding have not been evaluated. The effect of maximizing the audible bandwidth on speech recognition for a group of listeners with normal hearing is described. Design: Nonword recognition was measured with 20 normal-hearing adults. Three audiograms with different high-frequency thresholds were used to create conditions with varying high-frequency audibility. Bandwidth was manipulated using three conditions for each audiogram: conventional processing, the manufacturer’s default compression parameters, and compression parameters that optimized bandwidth. Results: Nonlinear frequency compression optimized to provide the widest audible bandwidth improved nonword recognition compared with both conventional processing and the default parameters. Conclusions: These results showed that using the widest audible bandwidth maximized speech identification when using nonlinear frequency compression. Future studies should apply these methods to listeners with hearing loss to demonstrate efficacy in clinical populations.