Blind modeling of binaural unmasking of speech in stationary maskers

Abstract

The equalization cancellation (EC) model predicts the binaural masking level difference by equalizing interaural differences in level and time and increasing the signal-to-noise ratio (SNR) using destructive and constructive interferences. The EC model has been successfully combined with the speech intelligibility index (SII) to predict binaural speech intelligibility. Here a blind EC model is introduced that relies solely on the mixture of speech and noise, replacing the unrealistic requirement of the separated clean speech and noise signals in previous versions. The model uses two parallel EC paths, which either maximize or minimize the EC output level in each frequency band. If SNR is negative, minimization improves the SNR by removing the interferer component from the mixed signal. If SNR is positive, maximization improves the SNR by enhancing the target component. Either the minimizing or maximizing path in each frequency band is selected blindly based on envelope frequency-selective amplitude modula...