The effects on speech intelligibility of three different noise reduction algorithms (spectral subtraction, minimal mean squared error spectral estimation, and subspace analysis) were evaluated in two types of noise (car and babble) over a 12 dB range of signal-to-noise ratios (SNRs). Results from these listening experiments showed that most algorithms deteriorated intelligibility scores. Modeling of the results with a logit-shaped psychometric function showed that the degradation in intelligibility scores was largely congruent with a constant shift in SNR, although some additional degradation was observed at two SNRs, suggesting a limited interaction between the effects of noise suppression and SNR.

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