Using HDC to evaluate signal similarity for information masking

In the many studies done on informational masking, interfering speech reduces speech intelligibility. This effect is often used to secure privacy in public spaces. These applications require estimates of how much masking is required. In general, masking effects are estimated by using spectrum information as excitation patterns. However, estimates of informational masking can hardly be obtained by only using spectrum information. Therefore, we estimated the effects of informational masking using time-domain information. Then, we calculated the cepstra of the envelopes’ magnitude histograms. If these cepstra are different between the target and the masker, the signals are not similar in the time-domain. Furthermore, the effect of informational masking would be low. Therefore, we considered the histograms’ cepstra distances (HCD) to estimate signal similarities. The signal similarities in our first experiment were estimated using five maskers by utilizing the HCD. These maskers were random noise, music, female speech, male speech, and target speaker’s speech. Male and female speech were more similar to the target speech than music and noise. Also, the same speaker’s speech was the most similar in the set of maskers. A listening test was carried out in the second experiment to verify the HCD. A double masker was used in this experiment as an effective informational masker. It has similar characteristics to reversal speech. The listening test results suggest the double-masker’s masking effects has the same relation with HCD. This suggests informational masking can be estimated by signal similarity using the HCD.