原位-环境提取方法主客观比较的关联研究

The primary-ambient extraction is helpful to realize flexible spatial sound playback. The effects of different extraction methods need to be verified by subjective evaluation, which is time-consuming, inefficient and not conducive to adjust while operating. If objective comparison is correlated with subjective evaluation, using objective comparison rather than subjective evaluation can improve the efficiency of algorithms and ensure the reliability of the algorithm evaluation. This paper presents the objective comparisons and subjective evaluations on four typical extraction methods, which are Principal Component Analysis (PCA), Least-Squares (LS), Masking and Ambient Phase Estimation with a Sparsity constraint (APES). Extraction performance is quantified by two objective criteria, which are Error-to-Signal Ratio (ESR) and Inter-channel Cross Coherence (ICC). And the extracted components are also used in the binaural rendering to evaluate the sound quality and the sound image width by subjective evaluation. The results show that the extraction methods with less extraction errors can achieve better sound quality in binaural rendering, while the extracted ambient components with weaker inter-channel cross correlation can acquire wider sound images.