Effect of cochlear implant n-of-m strategy on signal-to-noise ratio below which noise hinders speech recognition

Abstract

Speech recognition was measured in 24 normal-hearing subjects for unprocessed speech and for speech processed by a cochlear implant Advanced Combination Encoder (ACE) coding strategy in quiet and at various signal-to noise ratios (SNRs). All signals were low- or high-pass filtered to avoid ceiling effects. Surprisingly, speech recognition performance plateaus at approximately 22 dB SNR for both speech types, implying that ACE processing has no effect on the upper limit of the effective SNR range. Speech recognition improved significantly above 15 dB SNR, suggesting that the upper limit used in the Speech Intelligibility Index should be reconsidered.

Pulsatile Gaussian-Enveloped Tones (GET) Vocoders for Cochlear-Implant Simulation

“…Some studies have proposed pulsatile vocoders using filtered carriers with strong periodicities including noise burst (Blamey et al, 1984a; Blamey et al, 1984b) and complex tones (Deeks and Carlyon, 2004; Hilkhuysen and Macherey, 2014; Mesnildrey et al, 2016). Instead of using filtered carriers, some CI manufacturers have provided software to directly map electrodograms to vocoded sounds (Ausili et al, 2019; Stam et al, 2019). In this study, a GET-based vocoder was proposed, theoretically analyzed, and evaluated for its performance on CI speech perception simulation.…”