Abstract
Cochlear implants can provide partial restoration of hearing, even with limited spectral resolution and loss of fine temporal structure, to severely deafened individuals. Studies have indicated that background noise has significant deleterious effects on the speech recognition performance of cochlear implant patients. This study investigates the effects of noise on speech recognition using acoustic models of two cochlear implant speech processors and several predictive signal-processing-based analyses. The results of a listening test for vowel and consonant recognition in noise are presented and analyzed using the rate of phonemic feature transmission for each acoustic model. Three methods for predicting patterns of consonant and vowel confusion that are based on signal processing techniques calculating a quantitative difference between speech tokens are developed and tested using the listening test results. Results of the listening test and confusion predictions are discussed in terms of comparisons between acoustic models and confusion prediction performance.
Highlights
The purpose of a cochlear implant is to restore some degree of hearing to a severely deafened individual
The speech recognition performance of individuals with cochlear implants is measured through listening tests conducted in controlled laboratory settings, which are not representative of the typical conditions in which the devices are used by the individuals in daily life
An approximately equivalent level of performance was achieved with both acoustic models on the consonant recognition test, with differences between scores at most SNRs not statistically significant
Summary
The purpose of a cochlear implant is to restore some degree of hearing to a severely deafened individual. The manner and extent to which noise affects cochlear implantee’s speech recognition can depend on individual characteristics of the patient, the cochlear implant device, and the structure of the noise and speech signals. Not all of these relationships are well understood. Particular speech processing strategies may be more resistant to the effects of certain types of noise, or noise in general Other devices parameters, such as the number of channels, number of stimulation levels, and compression mapping algorithms, have been shown to influence how speech recognition will be affected by noise [4, 5, 6]. With all of these interdependent factors, the relationship between noise and speech recognition is quite complex and requires careful study
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