Towards auditory attention decoding with noise-tagging: A pilot study
H. A. Scheppink S. Ahmadi P. Desain M. Tangermann J. Thielen
Auditory attention decoding (AAD) aims to extract from brain activity the
attended speaker amidst candidate speakers, offering promising applications for
neuro-steered hearing devices and brain-computer interfacing. This pilot study
makes a first step towards AAD using the noise-tagging stimulus protocol, which
evokes reliable code-modulated evoked potentials, but is minimally explored in
the auditory modality. Participants were sequentially presented with two Dutch
speech stimuli that were amplitude modulated with a unique binary pseudo-random
noise-code, effectively tagging these with additional decodable information. We
compared the decoding of unmodulated audio against audio modulated with various
modulation depths, and a conventional AAD method against a standard method to
decode noise-codes. Our pilot study revealed higher performances for the
conventional method with 70 to 100 percent modulation depths compared to
unmodulated audio. The noise-code decoder did not further improve these
results. These fundamental insights highlight the potential of integrating
noise-codes in speech to enhance auditory speaker detection when multiple
speakers are presented simultaneously.