Recently it has been shown to be possible to ascertain the target of a subject's attention in a cocktail party environment from single-trial (~60 s) electroencephalography (EEG) data. Specifically, this was shown in the context of a dichotic listening paradigm where subjects were cued to attend to a story in one ear while ignoring a different story in the other and were required to answer questions on both stories. This paradigm resulted in a high decoding accuracy that correlated with task performance across subjects. Here, we extend this finding by showing that the ability to accurately decode attentional selection in a dichotic speech paradigm is robust to the particular attention task at hand. Subjects attended to one of two dichotically presented stories under four task conditions. These conditions required subjects to 1) answer questions on the content of both stories, 2) detect irregular frequency fluctuations in the voice of the attended speaker 3) answer questions on both stories and detect frequency fluctuations in the attended story, and 4) detect target words in the attended story. All four tasks led to high decoding accuracy (~89%). These results offer new possibilities for creating user-friendly brain computer interfaces (BCIs).