Blind Multi-channel speech separation using spatial estimation in two-speaker environments

Abstract

This paper investigates the problem of speech separation from a mixture of two  speech signals without source localization information in a room environment. Due to the lack of source information, the use of spatial detector comes at an expense of permutation ambiguity. To solve the problem, a permutation alignment algorithm based on correlation is employed to group the beamformer outputs into the correct  sources. Evaluations using recordings from a real room environment show that the  proposed beamformer offers a good interference suppression level whilst maintaining a low distortion level of the desired source.