A Design of Far-Field Speaker Localization System Using Independent Component Analysis with Subspace Speech Enhancement

In this paper, we propose a design of far-field single speaker localization system including noisy speech separation and enhancement with two separated channel microphones. First, we perform noisy speech separation simulations using a fast-ICA (independent component analysis) with subspace-based speech enhancement. The fast-ICA can be used to separate the two original source signals-noise and speech from their mixtures. Subspace-based speech enhancement is then utilized to reduce the residual background noise of the separated speech. Second, we calculate time-difference-of-arrival (TDOA) estimation for five directions of both right and left sides in the horizontal plane to realize speaker localization. The TDOA method estimates the time delay difference between the incoming speech signals to microphones using the average magnitude difference function (AMDF) algorithm. Finally we evaluate the localization system under various noisy environments. The experimental results reveal that the applicability of a system with noisy speech separation and enhancement, particularly for the front directions.