An Investigation of Audibility Effects on Cochlear Implant Speech Perception Prediction.

Abstract

Output Signal to Noise Ratio (OSNR) is the Signal to Noise Ratio (SNR) at the output of a cochlear implant (CI) sound processor. Whereas other prediction metrics typically predict mean speech-in-noise test scores for a group of subjects, an OSNR-based model has been shown to accurately predict scores for individual CI recipients. The OSNR model was unable to predict scores for aggressive Ideal Binary Mask (IdBM) sound processing. This algorithm calculated Input Signal to Noise Ratio (ISNR), in each CI channel, and applied a gain function to suppress noise when a gain threshold was exceeded.The current study investigated the effect of IdBM processing on the separate speech and noise signals to determine whether audibility was affecting intelligibility. A novel metric, "OSNR and Power" (OSNRP), which combined the effect of the reduction in output speech power with OSNR, was proposed.It was found that the IdBM reduced the output speech level, likely causing audibility issues, at poor ISNRs. OSNRP accurately predicted individual speech-in-noise test scores for aggressive IdBM.The novel OSNRP metric has potential as a tool for calculating optimum configurations for sound processor parameter settings for individual CI recipients. We propose using a prescribed set of reference test conditions, the results of which can be utilized to predict outcomes when using alternative sound processing parameters and techniques, and to tailor them to the individual needs of individual CI recipients.