Abstract
Humans are able to localize the source of a sound. This enables them to direct attention to a particular speaker in a cocktail party. Psycho-acoustic studies show that the sensory cortices of the human brain respond to the location of sound sources differently, and the auditory attention itself is a dynamic and temporally based brain activity. In this work, we seek to build a computational model which uses both spatial and temporal information manifested in EEG signals for auditory spatial attention detection (ASAD). We propose an end-to-end spatiotemporal attention network, denoted as STAnet, to detect auditory spatial attention from EEG. The STAnet is designed to assign differentiated weights dynamically to EEG channels through a spatial attention mechanism, and to temporal patterns in EEG signals through a temporal attention mechanism. We report the ASAD experiments on two publicly available datasets. The STAnet outperforms other competitive models by a large margin under various experimental conditions. Its attention decision for 1-second decision window outperforms that of the state-of-the-art techniques for 10-second decision window. Experimental results also demonstrate that the STAnet achieves competitive performance on EEG signals ranging from 64 to as few as 16 channels. This study provides evidence suggesting that efficient low-density EEG online decoding is within reach. This study also marks an important step towards the practical implementation of ASAD in real life applications.
Highlights
Humans have the ability to focus the auditory attention on one speaker in a multi-speaker environment, or “cocktail party scenario” [1]
In view of the fact that brain activity is a temporal process, and the EEG signals are essentially non-linear time series data [36], we propose a temporal attention mechanism to capture the temporal characteristics of EEG
We propose an end-to-end spatiotemporal attention network, denoted as STAnet, to detect auditory spatial attention solely based on EEG signals
Summary
Humans have the ability to focus the auditory attention on one speaker in a multi-speaker environment, or “cocktail party scenario” [1]. People with hearing loss will find such situations are difficult. Modern hearing aids are developed for a better experience by applying noise suppression, these devices often fail in practice for unable to single out and enhance.
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