  Detecting auditory attention based on brain signals enables many everyday
applications, and serves as part of the solution to the cocktail party effect
in speech processing. Several studies leverage the correlation between brain
signals and auditory stimuli to detect the auditory attention of listeners.
Recently, studies show that the alpha band (8-13 Hz) EEG signals enable the
localization of auditory stimuli. We believe that it is possible to detect
auditory spatial attention without the need of auditory stimuli as references.
In this work, we use alpha power signals for automatic auditory spatial
attention detection. To the best of our knowledge, this is the first attempt to
detect spatial attention based on alpha power neural signals. We propose a
spectro-spatial feature extraction technique to detect the auditory spatial
attention (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. Our
comparative results show that this neural approach outperforms other
competitive models by a large margin in all test cases.
