BAST: Binaural Audio Spectrogram Transformer for Binaural Sound Localization. (arXiv:2207.03927v1 [cs.SD])

Accurate sound localization in a reverberation environment is essential for
human auditory perception. Recently, Convolutional Neural Networks (CNNs) have
been utilized to model the binaural human auditory pathway. However, CNN shows
barriers in capturing the global acoustic features. To address this issue, we
propose a novel end-to-end Binaural Audio Spectrogram Transformer (BAST) model
to predict the sound azimuth in both anechoic and reverberation environments.
Two modes of implementation, i.e. BAST-SP and BAST-NSP corresponding to BAST
model with shared and non-shared …

arxiv audio localization sound spectrogram transformer