The association study of objective and subjective comparison in primary-ambient extraction methods

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. Objective comparison is related to subjective evaluation. That is to say, using objective comparison reflects 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 standards, which are the Error-to-Signal Ratio (ESR) and the Inter-channel Coherence (IC). And the extracted components are also used in the binaural rendering to evaluate the quality and image width by subjective evaluation. The results show that the extraction methods with less extraction error have the ability to get better sound quality in binaural rendering, while ambient with weaker correlation can achieve wider sound image.