Ideal Time-Frequency Masking Algorithms Lead to Different Speech Intelligibility and Quality in Normal-Hearing and Cochlear Implant Listeners

Hearing impaired listeners using cochlear implants (CIs) suffer from a decrease in speech intelligibility (SI) in adverse listening conditions. Time-frequency masks are often applied to perform noise suppression in an attempt to increase SI. Two important masks are the so-called ideal binary mask (IBM) with its binary weights and the ideal Wiener filter (IWF) with its continuous weights. It is unclear which of the masks has the highest potential for SI and speech quality enhancement in CI users. In this study, both approaches for SI and quality enhancement were compared. The investigations were conducted in normal-hearing (NH) subjects listening to noise vocoder CI simulations and in CI users. The potential for SI improvement was assessed in a sentence recognition task with ideal mask estimates in multitalker babble and with an interfering talker. The robustness of the approaches was evaluated with simulated estimation errors. CI users assessed the speech quality in a preference rating. The IWF outperformed the IBM in NH listeners. In contrast, no significant difference was obtained in CI users. Estimation errors degraded SI in CI users for both approaches. In terms of quality, the IWF outperformed, slightly, the IBM processed signals. The outcomes of this study suggest that the mask pattern is not that crucial for CIs. Results of speech enhancement algorithms obtained with NH subjects listening to vocoded or normally processed stimuli do not translate to CI users. This outcome means that the effect of new strategies has to be quantified with the user group considered.