Representing the intelligibility advantage of ideal binary masking with the most energetic channels

This study investigates how the intelligibility advantage of ideal binary mask (IBM) processing in synthesizing speech is affected by the use of a small number of the most energetic channels. In experiment 1, IBM-processed Mandarin speech that had been corrupted by speech spectrum-shaped noise or two-talker babble was synthesized by using as few as four of the most energetic target-dominated channels at each frame. This approach provided intelligibility comparable to that of speech synthesized with all of the target-dominated channels. Experiments 2, 3, and 4 examined how the intelligibility advantage of IBM processing from experiment 1 was affected by the local SNR threshold, low-frequency region (LFR) cut-off frequency, and vowel-based segmentation, respectively. Experiments 2 and 3 showed that a threshold of 0 dB for local SNR and a cutoff of 3000 Hz for LFR were optimal choices for improving the intelligibility of IBM processing based on the most energetic channels. Experiment 4 found that the intelligibility advantage of IBM processing with the most energetic channels was preserved at the segmental level of vowel-only IBM-processed speech. Taken together, the results suggest that compared to IBM-processed speech synthesized with all of the target-dominated channels, Mandarin speech synthesized by selecting a small number of the most energetic target-dominated channels can achieve similar levels of intelligibility.