Factors affecting predicted speech intelligibility with cochlear implants in an auditory model for electrical stimulation

A model of the auditory response to stimulation with cochlear implants (CIs) was used to predict speech intelligibility in electric hearing. The model consists of an auditory nerve cell population that generates delta pulses as action potentials in response to temporal and spatial excitation with a simulated CI signal processing strategy. The auditory nerve cells are modeled with a leaky integrate-and-fire model with membrane noise. Refractory behavior is introduced by raising the threshold potential with an exponentially decreasing function. Furthermore, the action potentials are delayed to account for latency and jitter. The action potentials are further processed by a central model stage, which includes spatial and temporal integration, resulting in an internal representation of the sound presented. Multiplicative noise is included in the internal representations to limit resolution. Internal representations of complete word sets for a sentence intelligibility test were computed and classified using a Dynamic-Time-Warping classifier to quantify information content and to estimate speech intelligibility. The number of auditory nerve cells, the spatial spread of the electrodes' electric field, and the internal noise intensity were found to have a major impact on the modeled speech intelligibility, whereas the influence of refractory behavior, membrane noise, and latency and jitter was minor.