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Detecting auditory attention based on brain signals enables many everydayapplications, and serves as part of the solution to the cocktail party effectin speech processing. Several studies leverage the correlation between brainsignals and auditory stimuli to detect the auditory attention of listeners.Recently, studies show that the alpha band (8-13 Hz) EEG signals enable thelocalization of auditory stimuli. We believe that it is possible to detectauditory spatial attention without the need of auditory stimuli as references.In this work, we use alpha power signals for automatic auditory spatialattention detection. To the best of our knowledge, this is the first attempt todetect spatial attention based on alpha power neural signals. We propose aspectro-spatial feature extraction technique to detect the auditory spatialattention (left/right) based on the topographic specificity of alpha power.Experiments show that the proposed neural approach achieves 81.7% and 94.6%accuracy for 1-second and 10-second decision windows, respectively. Ourcomparative results show that this neural approach outperforms othercompetitive models by a large margin in all test cases.

Low-latency auditory spatial attention detection based on spectro-spatial features from EEG