Previous studies usually extract features from the modalities in independent modules, and then they concatenate the corresponding utterance representations from the acoustics and lexical features to feed into the next layers of their models.
we argue that a more natural way to understand emotions is to align lexical and acoustic information, which simulates the way humans process both modalities simultaneously.