Speech Intelligibility for Cochlear Implant Users with the MMSE Noise-Reduction Time-Frequency Mask

Abstract Cochlear implants (CI) are the most successful electronic prostheses for human beings. They almost completely restore the communication capability in profound-to-severe hearing losses under quiet conditions. However, noisy scenarios still impose critical intelligibility limitations. Time-frequency masks have been widely used to improve signal to noise conditions (SNR) and, as a consequence, increase the speech intelligibility. The most studied methods in the literature are the Binary mask (BM) and the Wiener filter (WF), which were not originally designed for this application. This work analyzes the performance of the minimum mean square error (MMSE) magnitude estimator for increasing intelligibility in CI applications. Objective measures and psychoacoustic experiments with normal hearing volunteers and vocoded signals, as well as CI users indicate that the MMSE method outperfoms the intelligibility performance obtained by both BM and WF time-frequency masks, especially in low SNR conditions (SNR