It is well established that cochlear implants (CIs) are able to provide many users with excellent speech recognition ability in quiet conditions; however, the ability to correctly identify speech in noisy conditions or appreciate music is generally poor for implant users with respect to normal-hearing listeners. This discrepancy has been hypothesized to be in part a function of the relative decrease in spectral information available to implant users [1, 2]. One method that has been proposed for increasing the amount of spectral information available to CI users is to include time-varying stimulation rate in addition to changes in the place of stimulation. However, previous implementations of multi-rate strategies have failed to result in an improvement in speech recognition over the clinically available, fixed-rate strategies [3,4]. It has been hypothesized that this lack of success was due to a failure to consider the underlying perceptual responses to multi-rate stimulation.

In this work, psychophysical experiments were implemented with the goal of achieving a better understanding of the interaction of place and rate of stimulation and the effects of duration and context on CI listeners' ability to detect changes in stimulation rate. Results from those experiments were utilized in the implementation of a tuned multi-rate sound processing strategy for implant users in order to potentially "tune" multi-rate strategies and improve speech recognition performance.

In an acute study with quiet conditions, speech recognition performance with a tuned multi-rate implementation was better than performance with a clinically available, fixed-rate strategy, although the difference was not statistically significant. These results suggest that utilizing time-varying pulse rates in a subject-specific implementation of a multi-rate algorithm may offer improvements in speech recognition over clinically available strategies. A longitudinal study was also performed to investigate the potential benefit from training to speech recognition. General improvements in speech recognition ability were observed as a function of time; however, final scores with the tuned multi-rate algorithm never surpassed performance with the fixed-rate algorithm for noisy conditions.

The ability to improve upon speech recognition scores for quiet conditions with respect to the fixed-rate algorithm suggests that using time-varying stimulation rates potentially provides additional, usable information to listeners. However, performance with the fixed-rate algorithm proved to be more robust to noise, even after three weeks of training. This lack of robustness to noise may be in part a result of the frequency estimation technique used in the multi-rate strategy, and thus more sophisticated techniques for real-time frequency estimation should be explored in the future.