Co-channel speaker identification using usable speech extraction based on multi-pitch tracking

Abstract

Recently, usable speech criteria have been proposed to extract minimally corrupted speech for speaker identification (SID) in co-channel speech. In this paper, we propose a new usable speech extraction method to improve the SID performance under the co-channel situation based on the pitch information obtained from a robust multi-pitch tracking algorithm [2]. The idea is to retain the speech segments that have only one pitch detected and remove the others. The system is evaluated on co-channel speech and results show a significant improvement across various target to interferer ratios (TIR) for speaker identification.