Formant feature extraction from electrodograms is robust to map parameter variation

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 (#corroborates, via linked claim)

Categorization

• XREF: connects to: Formant extraction from cochlear implant electrodograms stays robust across users at low noise — Dijk, Pim van, Physiology, Psychoacoustics and…, 1823; Sonograms visually expose vowel formants as enhanced frequency bands; Internal noise, not feature extraction, explains individual variation in model vowel identification

Broader Connections

• Formant extraction from cochlear implant electrodograms stays robust across users at low noise #corroborates (0.92) — Dijk, Pim van, Physiology, Psychoacoustics and…, 1823
• Internal noise, not feature extraction, explains individual variation in model vowel identification #complicates (0.78)