Position-Dependent Crosstalk Cancellation Using Space Partitioning

Abstract

The present study tested a new stereo playback system that effectively cancels cross-talk signals at an arbitrary listening position. Such a playback system was implemented by integrating listener position tracking techniques and crosstalk cancellation techniques. The entire listening space was partitioned into a number of non-overlapped cells and a crosstalk cancellation filter was assigned to each cell. The listening space partitions and the corresponding crosstalk cancellation filters were constructed by maximizing the average channel separation ratio (CSR). Since the proposed method employed cell-based crosstalk cancellation, estimation of the exact position of the listener was not necessary. Instead, it was only necessary to determine the cell in which the listener was located. This was achieved by simply employing an artificial neural network (ANN) where the time delay to each pair of microphones was used as the ANN input and the ANN output corresponded to the index of cells. The experimental results showed that more than 95% of the experimental listening space had a CSR ≥ 10 dB when the number of clusters exceeded 12. Under these conditions, the correlation between the true directions of the virtual sound sources and the directions recognized by the subjects was greater than 0.9.