Data-driven clustering of 70,557 audiograms reveals distinct audiometric configurations that better reflect variability in speech perception, especially in noise, than pure-tone averages, advancing precision audiology and individualized rehabilitation strategies.
The effect of masker type and cochlear implant speech processing strategy on speech intelligibility is investigated with typical-hearing listeners using vocoding as a simulation of cochlear implant processing.
Does applying dynamic range compression separately to speech and noise improve intelligibility compared to joint compression, when using separated sources in non-stationary noise?
This study explored the validation of using artificial intelligence (AI) methods to improve the efficiency and accuracy of speech intelligibility assessment for children.