Estimation of vowel recognition with cochlear implant simulations.
Because there are many parameters in the cochlear implant (CI) device that can be optimized for individual patients, it is important to estimate a parameter's effect before patient evaluation. In this paper, Mel-frequency cepstrum coefficients (MFCCs) were used to estimate the acoustic vowel space for vowel stimuli processed by the CI simulations. The acoustic space was then compared to vowel recognition performance by normal-hearing subjects listening to the same processed speech. Five CI speech processor parameters were simulated to produce different degree of spectral resolution, spectral smearing, spectral warping, spectral shifting, and amplitude distortion. The acoustic vowel space was highly correlated with normal hearing subjects' vowel recognition performance for parameters that affected the spectral channels and spectral smearing. However, the acoustic vowel space was not significantly correlated with perceptual performance for parameters that affected the degree of spectral warping, spectral shifting, and amplitude distortion. In particular, while spectral warping and shifting did not significantly reshape the acoustic space, vowel recognition performance was significantly affected by these parameters. The results from the acoustic analysis suggest that the CI device can preserve phonetic distinctions under conditions of spectral warping and shifting. Auditory training may help CI patients better perceive these speech cues transmitted by their speech processors.
Liu
Chuping
C
Department of Electrical Engineering, University of Southern California, Los Angeles, CA 90007, USA. cliu@hei.org
Fu
Qian-Jie
QJ
D000328:Adult; D000465:Algorithms; D003054:Cochlear Implants; D003198:Computer Simulation; D017076:Computer-Aided Design; D012048:Correction of Hearing Impairment / Q000379:methods; D004867:Equipment Design; D019544:Equipment Failure Analysis; D005260:Female; D006311:Hearing Disorders / Q000503:physiopathology*; D006801:Humans; D008297:Male; D008954:Models, Biological; D013018:Sound Spectrography / Q000379:methods*; D013067:Speech Perception; D013068:Speech Production Measurement / Q000379:methods*; D013813:Therapy, Computer-Assisted / Q000379:methods*