  This paper presents a joint source separation algorithm that simultaneously
reduces acoustic echo, reverberation and interfering sources. Target speeches
are separated from the mixture by maximizing independence with respect to the
other sources. It is shown that the separation process can be decomposed into
cascading sub-processes that separately relate to acoustic echo cancellation,
speech dereverberation and source separation, all of which are solved using the
auxiliary function based independent component/vector analysis techniques, and
their solving orders are exchangeable. The cascaded solution not only leads to
lower computational complexity but also better separation performance than the
vanilla joint algorithm.
