  We propose a method for joint multichannel speech dereverberation with two
spatial-aware tasks: direction-of-arrival (DOA) estimation and speech
separation. The proposed method addresses involved tasks as a sequence to
sequence mapping problem, which is general enough for a variety of front-end
speech enhancement tasks. The proposed method is inspired by the excellent
sequence modeling capability of bidirectional encoder representation from
transformers (BERT). Instead of utilizing explicit representations from
pretraining in a self-supervised manner, we utilizes transformer encoded hidden
representations in a supervised manner. Both multichannel spectral magnitude
and spectral phase information of varying length utterances are encoded.
Experimental result demonstrates the effectiveness of the proposed method.
