Estimation of binaural intelligibility using the frequency-weighted segmental SNR of stereo channel signals

Abstract

Most existing objective intelligibility prediction methods predict monaural intelligibility using monaural signals. These methods do not consider that a human can easily distinguish sounds arriving from different directions by sound heard in both ears. Therefore, intelligibility prediction using binaural signals that take this into account is necessary. Accordingly, speech samples with various source locations were prepared using binaural simulation. Subjective measurement tests were carried out on these samples. The frequency-weighted segmental SNR (fwSNRseg) was obtained using two different models for comparison: 1) a monaural model, which simply combines signals in both channels into one, and 2) the simple better ear model which uses the channel with the better SNR. Binaural intelligibility is estimated by applying regression analysis on the fwSNRseg and the subjective measurement results. Intelligibility was predicted by applying the resultant regression function on fwSNRseg of the test sample. We compared the estimation precision of the two models with binaural signals. The estimation precision of the better ear model yielded higher correlation with subjective scores than that of the monaural model by approximately 0.2 in a closed test as well as two open sets.