Selectively attending to a particular speaker in the presence of interfering speakers is a challenging task, especially for hearing impaired listeners. In this context, beamforming algorithms, which selectively enhance the speech signal from the attended speaker, have been proposed to provide assistence.

Within my PhD, I investigate the effect of these beamforming algorithms on the neural processing of the unattended speech signal. Therefore, it is important to note that in general, one is unable to comprehend the content of an unattended speaker unless it contains salient or personally relevant stimuli such as one's own name. As beamforming algorithms are designed to enhance the attended speaker, it remains unkown to which extent one is still able to notice relevant stimuli if these are uttered by an unattended speaker who is attenuated by the beamforming algorithm. In order to examine this question, I investigate neural event detection methods as well as attention-modulated neural signatures using EEG.