An efficient and effective stereo vocal extraction algorithm is presented, which combines two existing approaches. A Nearest Neighbours Median Filtering algorithm is used to separate the vocals and the instrumental backing track from the stereo mixture. The separated vocal track is then passed through a mask generated by the Adress algorithm and high-pass filtered to extract the vocals. The separated instrumental backing track is then improved by adding to it the residual backing track energy extracted by Adress. Also investigated is a variant on this algorithm which uses a difference spectrogram to calculate the nearest neighbours. The effectiveness of these algorithms is then demonstrated on a test dataset, and results show that the proposed algorithms give performance comparable to the state of the art, but at a low computational cost.