The Relative Transfer Matrix (ReTM), recently introduced as a generalization of the relative transfer function for multiple receivers and sources, shows promising performance when applied to speech enhancement and speaker separation in noisy environments. Blindly estimating the ReTM of sound sources by exploiting the covariance matrices of multichannel recordings is highly beneficial for practical applications. In this paper, we use covariance subtraction to present a flexible and practically viable method for estimating the ReTM for a select set of independent sound sources. To show the versatility of the method, we validated it through a speaker separation application under reverberant conditions. Separation performance is evaluated at low signal-to-noise ratio levels in comparison with existing ReTM-based and relative transfer function-based estimators, in both simulated and real-life environments.

翻译：相对传递矩阵（ReTM）作为多接收器与多声源场景下相对传递函数的推广，近期被提出并在噪声环境下的语音增强与说话人分离任务中展现出优异性能。利用多通道录音的协方差矩阵对声源的ReTM进行盲估计，在实际应用中具有重要价值。本文提出一种基于协方差减法的灵活且实用的方法，用于估计一组选定独立声源的ReTM。为验证方法的普适性，我们在混响环境下通过说话人分离应用进行了测试。在仿真与真实场景中，该方法在低信噪比条件下的分离性能均优于现有的基于ReTM及基于相对传递函数的估计器。