High-speed separation of anechoic mixtures of speech signals using fusion of iterative and closed-forms separation method

摘要

We introduce the fusion of iterative and closed-forms separation (FICS) method for high-speed separation of anechoic mixed speech signals. This method is performed in two stages: 1) iterative-form separation and 2) closed-form separation. This algorithm significantly improves the separation quality simply due to incorporating only some specific frequency bins into computations. We apply the FICS method to the frequency-domain independent component analysis (ICA) to evaluate its performance in increasing the signal separation speed for anechoic mixtures. Simulation results show that for speech signals and anechoic conditions, the proposed algorithm is on average 65 times faster than ICA while preserving the separation quality. It also outperforms FastICA, JADE, and SOBI in terms of separation quality and speed.