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A previous signal processing algorithm that aimed to enhance spectral changes(SCE) over time showed benefit for hearing-impaired (HI) listeners to recognizespeech in background noise. In this work, the previous SCE was manipulated toperform on target-dominant segments, rather than treating all frames equally.Instantaneous signal-to-noise ratios (SNRs) were calculated to determinewhether the segments should be processed. Initially, the ideal SNR calculatedby the knowledge of premixed signals was introduced to the previous SCEalgorithm (SCE-iSNR). Speech intelligibility (SI) and clarity preference weremeasured for 12 HI listeners in steady speech-spectrum noise (SSN) and six-talkspeech (STS) maskers, respectively. The results showed the SCE-iSNR algorithmimproved SI significantly for both maskers at high signal-to-masker ratios(SMRs) and for STS masker at low SMRs, while processing effect on speechquality was small. Secondly, the estimated SNR obtained from real mixtures wasused, resulting in another SCE-eSNR. SI and subjective rating on naturalnessand speech quality were tested for 7 HI subjects. The SCE-eSNR algorithm showedimproved SI for SSN masker at high SMRs and for STS masker at low SMRs, as wellas better naturalness and speech quality for STS masker. The limitations ofapplying the algorithms are discussed.

Spectral-change enhancement with prior SNR for the hearing impaired