Comparisons of speech enhancement algorithms for normal and sensorineural hearing impairment listeners

Background noise is one of the major complaints of not only hearing impaired persons but also normal listeners, because the hearing aid amplifies both speech signal and background noise. This paper describes the results of two experiments in which speech recognition performance was determined for listeners with normal hearing and sensorineural hearing loss, while listening in noise. First, we evaluated speech recognition ability in various speech-to-noise ratios and types of noise. Next, speech enhancement algorithms reducing background noise were evaluated to improve speech intelligibility for sensorineural hearing impairment listeners. We tested three noise reduction methods using single-microphone, such as transformed spectrum subtraction, Wiener filter method, and maximum likelihood envelope estimation. Their responses in background noise were investigated and compared with those by the speech enhancement algorithm presented. The methods improved speech recognition test score for the sensorineural hearing impaired listeners, but not for normal listeners. The results suggest the speech enhancement algorithm may work in synergy with the gain function for the greater SNR improvement as the pre-processing algorithm of digital hearing aids.