Dynamic time warping with path control and non-local cost

Abstract

Dynamic Time Warping (DTW) is a Dynamic Programming technique widely used for solving time-alignment problems. The classical DTW constrains only the first derivative of the warping function, hence allowing no direct control over the warping function curvature. Moreover, it implicitly assumes-inappropriately for some applications-that the noise is white. We propose a multi-dimensional Dynamic-Programming technique which can efficiently solve time-warping optimization problems involving colored noise, and allows control over the warping function curvature. The technique is demonstrated for the co-channel speech separation problem. Applications employing DTW can benefit from the new technique, which offers improved accuracy and robustness in the presence of colored noise and competing speech.