Phase estimation for signal reconstruction in single-channel speech separation

Single-channel speech separation algorithms frequently ignore the issue of accurate phase estimation while reconstructing the enhanced signal. Instead, they directly employ the mixed-signal phase for signal reconstruction which leads to undesired traces of the interfering source in the target signal. In this paper, assuming a given knowledge of signal spectrum amplitude, we present a solution to estimate the phase information for signal reconstruction of the sources from a single-channel mixture observation. We first investigate the effectiveness of the proposed phase estimation method employing known magnitude spectra of sources as an ideal case. We further relax the ideal signal spectra assumption by perturbing the clean signal spectra via Gaussian noise. The results show that for both scenarios, ideal and noisy magnitude signal spectra, the proposed phase estimation approach offers improved signal reconstruction accuracy, segmental SNR and PESQ compared to benchmark methods, and those neglecting the phase information.