  The purpose of speech dereverberation is to remove quality-degrading effects
of a time-invariant impulse response filter from the signal. In this report, we
describe an approach to speech dereverberation that involves joint estimation
of the dry speech signal and of the room impulse response. We explore deep
learning models that apply to each task separately, and how these can be
combined in a joint model with shared parameters.
