Time-shifted principal component analysis based cue extraction for stereo audio signals

In spatial audio analysis-synthesis, one of the key issues is to decompose a signal into cue and ambient components based on their spatial features. Principal component analysis (PCA) has been widely employed in cue extraction. However, the performance of PCA based cue extraction is highly dependent on the assumptions of the input signal model. One of these assumptions is the input signal contains highly correlated cue at zero lag. However, this assumption is often unmet. To overcome this problem, time shifted PCA is proposed in this paper, which involves time-shifting the input signal according to the estimated inter-channel time difference (ITD) of the input signal before cue extraction. From our simulation and listening tests results, the proposed method is found to be superior to the conventional PCA based cue extraction method.