title: Representing the intelligibility advantage of ideal binary masking with the most energetic channels.
abstract: 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.
authors.affiliation: Department of Electrical and Electronic Engineering, Southern University of Science and Technology, Shenzhen, China.
authors.forename: Fei
authors.initials: F
authors.lastname: Chen