Real-Time Moving Blind Source Extraction Based on Constant Separating Vector and Auxiliary Function Technique

Abstract

We propose a novel online algorithm for moving blind source extraction (BSE). The original algorithm is based on the recently proposed constant separating vector mixing model with batch auxiliary-function-based independent vector extraction (CSV-AuxIVE). The CSV-AuxIVE is not suitable for some devices that require real-time processing. In this case, we propose the online-CSV-AuxIVE, which only needs to know part of the mixed signal to process the observed signal sequentially. Then, we verified the effectiveness of the proposed method on a specific task of extracting moving two-speaker signals. In the experiment, the online-CSV-AuxIVE is compared with the online-AuxIVA. The result shows that under the same conditions of the source of interest (SOI), the average source-to-distortion ratio (SDR) of online-CSV-AuxIVE is approximately 1.5 dB higher than that of online-AuxIVA regardless of the changes in the range and speed of the interference (IR).