IMPROVING CONSONANT INTELLIGIBILITY FOR INERAID PATIENTS FIT WITH CONTINUOUS INTERLEAVED SAMPLING (CIS) PROCESSORS BY ENHANCING CONTRAST AMONG CHANNEL OUTPUTS
Mf. Dorman et Pc. Loizou, IMPROVING CONSONANT INTELLIGIBILITY FOR INERAID PATIENTS FIT WITH CONTINUOUS INTERLEAVED SAMPLING (CIS) PROCESSORS BY ENHANCING CONTRAST AMONG CHANNEL OUTPUTS, Ear and hearing, 17(4), 1996, pp. 308-313
Objective: In Experiment 1 the objective was to determine whether pati
ents who have been implanted with the Ineraid electrode array perform
better on tests of consonant identification when signals are processed
through a continuous interleaved sampling (CLS) processor than when s
ignals are processed through an analogue (Ineraid) processor. In Exper
iment 2 the objective was to determine, for patients using the CIS str
ategy, whether identification accuracy for stop consonant place of art
iculation could be improved by enhancing differences in the patterns o
f the signal processor channel outputs. Design: In Experiment 1, 16 co
nsonants were presented in VCV format for identification. In Experimen
t 1 the CIS patients evidenced difficulty in identifying /p t k/. Ther
efore, in Experiment 2 the voiceless stop consonants were presented in
two stimulus conditions. In one, the stimuli were unfiltered In the o
ther, the stimuli were individually filtered so as to enhance the diff
erences in channel outputs for /p/, /t/, and /k/. Results: In Experime
nt 1 the patients performed better with CIS processors than with analo
gue processors. In Experiment 2 the ''enhanced' stimuli were identifie
d with better accuracy than were the unfiltered stimuli. Conclusions:
We confirm that Ineraid patients achieve higher scores on tests of con
sonant identification when using a CLS processor than when using an an
alogue processor. Errors in identification of stop consonant place of
articulation, when using a CIS processor, are due to the similarity in
the patterns of the processor's channel outputs. By showing that cons
onant intelligibility can be improved by filtering, we show that we ha
ve not reached the limit of speech understanding that can be supported
by the population of neural elements remaining in our patients' audit
ory systems.