BLIND MULTI-CHANNEL SPEECH SEPARATION USING SPATIAL ESTIMATION IN TWO-SPEAKER ENVIRONMENTS
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.
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