This paper explores the feasibility of using synchronization of speech mixtures prior to blind sparse source separation methods in order to improve their results. Broadly, methods that assume sparse sources use level and phase differences between mixtures as their features, and they separate signals from them. If each mixture is considerably delayed with respect to the rest of them, the information extracted from these differences can be wrong. With this idea in mind, this paper will focus on using Time Delay Estimation algorithms in order to synchronize the mixtures and observing the improvement that it provokes in a Blind Sparse Source Separation algorithm. The results obtained show the feasibility of using synchronization of the speech mixtures.
Click to purchase paper as a non-member or login as an AES member. If your company or school subscribes to the E-Library then switch to the institutional version. If you are not an AES member and would like to subscribe to the E-Library then Join the AES!
This paper costs $33 for non-members and is free for AES members and E-Library subscribers.