Speech Perception With Combined Electric-Acoustic Stimulation: A Simulation and Model Comparison.

Abstract

The aim of this study is to simulate speech perception with combined electric-acoustic stimulation (EAS), verify the advantage of combined stimulation in normal-hearing (NH) subjects, and then compare it with cochlear implant (CI) and EAS user results from the authors' previous study. Furthermore, an automatic speech recognition (ASR) system was built to examine the impact of low-frequency information and is proposed as an applied model to study different hypotheses of the combined-stimulation advantage. Signal-detection-theory (SDT) models were applied to assess predictions of subject performance without the need to assume any synergistic effects. Speech perception was tested using a closed-set matrix test (Oldenburg sentence test), and its speech material was processed to simulate CI and EAS hearing. A total of 43 NH subjects and a customized ASR system were tested. CI hearing was simulated by an aurally adequate signal spectrum analysis and representation, the part-tone-time-pattern, which was vocoded at 12 center frequencies according to the MED-EL DUET speech processor. Residual acoustic hearing was simulated by low-pass (LP)-filtered speech with cutoff frequencies 200 and 500 Hz for NH subjects and in the range from 100 to 500 Hz for the ASR system. Speech reception thresholds were determined in amplitude-modulated noise and in pseudocontinuous noise. Previously proposed SDT models were lastly applied to predict NH subject performance with EAS simulations. NH subjects tested with EAS simulations demonstrated the combined-stimulation advantage. Increasing the LP cutoff frequency from 200 to 500 Hz significantly improved speech reception thresholds in both noise conditions. In continuous noise, CI and EAS users showed generally better performance than NH subjects tested with simulations. In modulated noise, performance was comparable except for the EAS at cutoff frequency 500 Hz where NH subject performance was superior. The ASR system showed similar behavior to NH subjects despite a positive signal-to-noise ratio shift for both noise conditions, while demonstrating the synergistic effect for cutoff frequencies ≥300 Hz. One SDT model largely predicted the combined-stimulation results in continuous noise, while falling short of predicting performance observed in modulated noise. The presented simulation was able to demonstrate the combined-stimulation advantage for NH subjects as observed in EAS users. Only NH subjects tested with EAS simulations were able to take advantage of the gap listening effect, while CI and EAS user performance was consistently degraded in modulated noise compared with performance in continuous noise. The application of ASR systems seems feasible to assess the impact of different signal processing strategies on speech perception with CI and EAS simulations. In continuous noise, SDT models were largely able to predict the performance gain without assuming any synergistic effects, but model amendments are required to explain the gap listening effect in modulated noise.