Security monitoring based on joint automatic speaker recognition and blind source separation
Michele Scarpiniti, Fabio Garzia · 2014
The aim of this paper is to introduce an enhanced approach for standard Automatic Speaker Recognition (ASR) systems in noisy environment in conjunction with a Blind Source Separation (BSS) algorithm. This latter is able to discern between interfering noise signals and the reference speech signal, hence it can be consider as a necessary preprocessing step. The main problem of the proposed approach lies in the not removable ambiguities typically of the BSS algorithms. In order to overcome to this drawback, a geometrical constraint is also added to the learning algorithm. A practical example shows the effectiveness of the proposed approach in terms of recognition accuracy.