Formant extraction from cochlear implant electrodograms stays robust across users at low noise

Evidence

From the modelling results it can be observed that maximum performance is achieved for SCE factors 2 and 4. The other interesting aspect is that there is no difference in performance across the five different virtual CI users for “Noise Factor” 0.001 (Fig. 2a ). That means that the feature extraction (i.e. the extraction of the formants) is robust to the different electrodograms of each virtual CI user. Differences in performance between the five virtual CI users can only be observed for “Noise Factor” 0.1 and 0.5, meaning that the “jnd noise” is the only parameter explaining the differences. — Dijk, Pim van, Physiology, Psychoacoustics and…, 1823

From the modelling results it can be observed that maximum performance is achieved for SCE factors 2 and 4. The other interesting aspect is that there is no difference in performance across the five different virtual CI users for “Noise Factor” 0.001 (Fig. 2a ). That means that the feature extraction (i.e. the extraction of the formants) is robust to the different electrodograms of each virtual CI user. Differences in performance between the five virtual CI users can only be observed for “Noise Factor” 0.1 and 0.5, meaning that the “jnd noise” is the only parameter explaining the differences. From the MPI modelling results we decided to use SCE factors 2 and 4 (equivalent to increasing the original spectral contrast of the spectrum by 3 and by 5 in a dB scale) to be investigated in CI users. — Dijk, Pim van, Physiology, Psychoacoustics and…, 1857

Categorization

• QUESTION: What exactly is ‘jnd noise’ in the virtual CI model, and why does it only explain differences at higher noise factors?
• corroborated: 3 independent passages support this claim — Dijk, Pim van, Physiology, Psychoacoustics and…, 1823; Dijk, Pim van, Physiology, Psychoacoustics and…, 1857