Cochlear implants are able to restore some degree of hearing to deafened individuals; however implant users are particularly susceptible to background noise. The effect of noise can be assessed using vowel and consonant confusions measured in listening experiments. The paper presents three signal processing methods developed to predict patterns in vowel and consonant confusion in noise for cochlear implant users. Prediction performance is tested using the results of a listening experiment conducted with acoustic models of two cochlear implant speech processors and normal hearing subjects. Confusion prediction is based on prediction metrics calculated using each method's unique representation of the speech tokens.
['Jeremiah J. Remus', 'Leslie M. Collins']
Vowel and consonant confusion in noise by cochlear implant subjects: predicting performance using signal processing techniques