Permutation Alignment Of Frequency-Domain Ica By The Maximization Of Intra-Source Envelope Correlations

This paper presents a novel method for solving the permuta- tion ambiguity of frequency-domain independent component analysis based on source signal envelope correlation maxi- mization. The proposed method is developed for blind source separation with high sampling frequency and significant spa- tial aliasing. We propose a method that analyzes the source envelope using a rank-one singular value decomposition (SVD) applied to an initial source magnitude spectrogram obtained by a time difference of arrival (TDoA) based per- mutation alignment method. The permutation for frequencies with incoherent TDoA are corrected by maximizing the cross- correlation of the SVD analyzed source activation vector and each independent component magnitude envelope. We evalu- ate the separation quality using real high sampling frequency speech captures and the proposed method is found to improve the separation over the baseline algorithm.

Blind Source Separation; Independent Component Analysis; Permutation Alignment