Experienced Adult Cochlear Implant Users Show Improved Speech Recognition When Target Fitting Parameters Are Applied

The aim of the present study was to investigate whether prediction models built by de Graaff et al. (2020 ) can be used to improve speech recognition in experienced adult postlingual implanted Cochlear CI users. de Graaff et al. (2020 ) found relationships between elevated aided thresholds and a not optimal electrical dynamic range (<50 CL or >60 CL), and poorer speech recognition in quiet and in noise. The primary hypothesis of the present study was that speech recognition improves both in quiet and in noise when the sound processor is refitted to match targets derived from the prediction models from de Graaff et al. (2020 ). A second hypothesis was that subjectively, most of the CI users would find the new setting too loud because of an increase in C levels, and therefore, prefer the old settings.