Comparison of the Spectral-Temporally Modulated Ripple Test With the Arizona Biomedical Institute Sentence Test in Cochlear Implant Users.

Objectives: Although speech perception is the gold standard for measuring cochlear implant (CI) users' performance, speech perception tests often require extensive adaptation to obtain accurate results, particularly after large changes in maps. Spectral ripple tests, which measure spectral resolution, are an alternate measure that has been shown to correlate with speech perception. A modified spectral ripple test, the spectral-temporally modulated ripple test (SMRT) has recently been developed, and the objective of this study was to compare speech perception and performance on the SMRT for a heterogeneous population of unilateral CI users, bilateral CI users, and bimodal users.

Design: Twenty-five CI users (eight using unilateral CIs, nine using bilateral CIs, and eight using a CI and a hearing aid) were tested on the Arizona Biomedical Institute Sentence Test (AzBio) with a +8 dB signal to noise ratio, and on the SMRT. All participants were tested with their clinical programs.

Results: There was a significant correlation between SMRT and AzBio performance. After a practice block, an improvement of one ripple per octave for SMRT corresponded to an improvement of 12.1% for AzBio. Additionally, there was no significant difference in slope or intercept between any of the CI populations.

Conclusion: The results indicate that performance on the SMRT correlates with speech recognition in noise when measured across unilateral, bilateral, and bimodal CI populations. These results suggest that SMRT scores are strongly associated with speech recognition in noise ability in experienced CI users. Further studies should focus on increasing both the size and diversity of the tested participants, and on determining whether the SMRT technique can be used for early predictions of long-term speech scores, or for evaluating differences among different stimulation strategies or parameter settings.