Abstract
We have previously identified neurons tuned to spectral contrast of wideband sounds in auditory cortex of awake marmoset monkeys. Because additive noise alters the spectral contrast of speech, contrast-tuned neurons, if present in human auditory cortex, may aid in extracting speech from noise. Given that this cortical function may be underdeveloped in individuals with sensorineural hearing loss, incorporating biologically-inspired algorithms into external signal processing devices could provide speech enhancement benefits to cochlear implantees. In this study we first constructed a computational signal processing algorithm to mimic auditory cortex contrast tuning. We then manipulated the shape of contrast channels and evaluated the intelligibility of reconstructed noisy speech using a metric to predict cochlear implant user perception. Candidate speech enhancement strategies were then tested in cochlear implantees with a hearing-in-noise test. Accentuation of intermediate contrast values or all contrast values improved computed intelligibility. Cochlear implant subjects showed significant improvement in noisy speech intelligibility with a contrast shaping procedure.
Highlights
Hearing-impaired individuals in general, and cochlear implantees in particular, can often comprehend speech comparably to normal-hearing listeners in the absence of noise, but exhibit poorer-than-normal performance in noisy environments (Friesen et al, 2001; Nie et al, 2005)
We hypothesized based upon our previous neurophysiological findings that emphasizing mainly the intermediate contrast values could result in a substantial increase in speech intelligibility
Using our contrast-shaping algorithm we found that a substantial increase in computed noisy speech intelligibility can potentially be obtained by accentuating primarily the intermediate contrasts (4–8 decibels of standard deviation (dB SD)) (Figures 5–7)
Summary
Hearing-impaired individuals in general, and cochlear implantees in particular, can often comprehend speech comparably to normal-hearing listeners in the absence of noise, but exhibit poorer-than-normal performance in noisy environments (Friesen et al, 2001; Nie et al, 2005). Research into artificially compensating for spectral contrast deficits has resulted in a class of algorithms that perform a global spectral contrast enhancement. These algorithms represent signal processing strategies where peaks in the shortterm signal spectrum are stretched relative to the troughs (i.e., the spectral variance is uniformly increased as a function of frequency). Previous studies evaluating the ability of spectral contrast enhancement to improve the intelligibility of noisy speech have demonstrated some potential benefit of this noise-reduction strategy for cochlear implant users and variable results for other subjects (Bunnell, 1990; Simpson et al, 1990; Stone and Moore, 1992; Baer et al, 1993; Ribic et al, 1996; Munoz et al, 1999; Loizou and Poroy, 2001; Lyzenga et al, 2002; Yang et al, 2003)
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