Spectral-change Enhancement with prior SNR for the Hearing Impaired
* Presenting author
A previous signal processing algorithm that aimed to enhance spectral changes (SCE) over time showed benefit for hearing-impaired (HI) listeners to recognize speech in background noise. In this work, the previous SCE was manipulated to perform on target-dominant segments, rather than treating all frames equally. Instantaneous signal-to-noise ratios (SNRs) were calculated to determine whether the segments should be processed. Initially, the ideal SNR calculated by the original signals before mixed was introduced to the previous SCE algorithm (SCE-iSNR). Speech intelligibility (SI) and clarity preference were measured for the speech with steady speech-spectrum noise (SSN) and six-talk speech (STS) maskers across 12 HI listeners. Results showed the SCE-iSNR processing improved SI significantly for both maskers at high signal-to-masker ratios (SMRs) and for STS masker at low SMRs, while processing effect on speech quality was small. In addition, the estimated SNR obtained from real mixtures was used (SCE-eSNR). SI and subjective rating on naturalness and speech quality were tested for 7 HI subjects. The SCE-eSNR algorithm showed benefit on SI for SSN masker at high SMRs and for STS masker at low SMRs, and on naturalness and speech quality for STS masker. The limitations of applying the algorithms are discussed.