Abstract
The spectral ripple discrimination task is a psychophysical measure that has been found to correlate with speech recognition in listeners with cochlear implants (CIs). However, at ripple densities above a critical value (around 2 RPO, but device-specific), the sparse spectral sampling of CI processors results in stimulus distortions resulting in aliasing and unintended changes in modulation depth. As a result, spectral ripple thresholds above a certain number are not ordered monotonically along the RPO dimension and thus cannot be considered better or worse spectral resolution than each other, thus undermining correlation measurements. These stimulus distortions are not remediated by changing stimulus phase, indicating these issues cannot be solved by spectrotemporally modulated stimuli. Speech generally has very low-density spectral modulations, leading to questions about the mechanism of correlation between high ripple thresholds and speech recognition. Existing data showing correlations between ripple discrimination and speech recognition include many observations above the aliasing limit. These scores should be treated with caution, and experimenters could benefit by prospectively considering the limitations of the spectral ripple test.