Evaluation of a self-generator method for initial filters of SIMO-ICA applied to blind separation of binaural sound mixtures

Blind separation of binaural mixed sounds using single-input multiple-output (SIMO)-model-based independent component analysis (SIMO-ICA) with self-generator for initial filter (SIMO-ICA-SG) is now being studied by the authors. This method contains frequency-domain ICA (FDICA-PB), single-talk detection, direction of arrival (DOA) estimation, head related transfer function (HRTF) matrix bank, and SIMO-ICA. This paper describes robustness of SIMO-ICA-SG against the mismatch of HRTF matrix bank. To evaluate it, the sound decomposition experiments are carried out under the real acoustic conditions. The experimental results reveal that the decomposition performance of the proposed method with mismatched HRTF matrix bank is superior to those of the conventional methods, and almost the same as those of the proposed method with matched one