Joint Online Multichannel Acoustic Echo Cancellation, Speech Dereverberation and Source Separation
This addresses the challenge of enhancing speech clarity in noisy environments for applications like teleconferencing, though it is incremental as it builds on existing independent component/vector analysis techniques.
The paper tackles the problem of simultaneously reducing acoustic echo, reverberation, and interfering sources in speech signals, achieving better separation performance and lower computational complexity through a cascaded algorithm compared to a vanilla joint approach.
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.