Among numerous blind source separation (BSS) methods, convolutive transfer function-based multichannel non-negative matrix factorization (CTF-MNMF) has demonstrated strong performance in highly reverberant environments by modeling multi-frame correlations of delayed source signals. However, its practical deployment is hindered by the high computational cost associated with the iterative projection (IP) update rule, which requires matrix inversion for each source. To address this issue, we propose an efficient variant of CTF-MNMF that integrates iterative source steering (ISS), a matrix inversion-free update rule for separation filters. Experimental results show that the proposed method achieves comparable or superior separation performance to the original CTF-MNMF, while significantly reducing the computational complexity.

翻译：在众多盲源分离方法中，基于卷积传递函数的多通道非负矩阵分解通过建模延迟源信号的多帧相关性，在强混响环境中展现出优越性能。然而，其实际应用受限于迭代投影更新规则带来的高计算成本，该规则需要对每个源进行矩阵求逆。为解决此问题，我们提出一种CTF-MNMF的高效变体，该方法融合了迭代源导向——一种无需矩阵求逆的分离滤波器更新规则。实验结果表明，所提方法在显著降低计算复杂度的同时，取得了与原始CTF-MNMF相当或更优的分离性能。