David McAlpine

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This study validates a novel approach to predict speech intelligibility for Cochlear Implant users (CIs) in rever-berant environments. More specifically, we explore the use of existing objective quality and intelligibility met-rics, applied directly to vocoded speech degraded by room reverberation, here assessed at ten different reverberation time (RT60)(More)
Our ability to detect prominent changes in complex acoustic scenes depends not only on the ear's sensitivity but also on the capacity of the brain to process competing incoming information. Here, employing a combination of psychophysics and magnetoencephalography (MEG), we investigate listeners' sensitivity in situations when two features belonging to the(More)
Cochlear implants (CIs) are devices capable of restoring hearing function in profoundly-deaf patients to an acceptable degree of performance. An essential processing step in any cochlear implant is frequency analysis, which is usually performed via banks of filters. Here, we simulate and test the suitability of different filters and filterbank architectures(More)
A measure to predict speech intelligibility in unilateral and bilateral cochlear implant (CI) users is proposed that does not need a priori information (i.e. is non-intrusive), such as the room acoustics. Such measure, termed BiSIMCI , combines an equalization-cancellation stage together with a modulation frequency estimation stage. Simulated and actual(More)
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