Few existing studies focus on the source separation problem with unknown numbers of signals, and how to evaluate the performances of the systems is not yet clear. We propose a solution with a fixed number of output channels to address these two problems, enabling it to avoid the dimensional disaster caused by the permutation problem induced by the alignment of outputs to targets. Specifically, we propose a two-step algorithm based on autoencoders and a new performance evaluation method for situations with mute channels. Experiments conducted on simulated mixtures of radiated ship noise show that the proposed solution can achieve similar separation performance to that attained with a known number of signals. The proposed algorithm achieved competitive performance as two algorithms developed for known numbers of signals, which is highly explainable and extensible and get the state of the art under this framework.

翻译：现有研究较少关注信号数量未知的源分离问题，且系统性能评估方法尚不明确。针对这两个问题，我们提出一种固定输出通道数的解决方案，通过避免输出与目标对齐产生的排列问题所导致的维度灾难。具体而言，我们提出基于自编码器的两步算法，并针对静默通道场景设计新型性能评估方法。在船舶辐射噪声混合模拟实验中的结果表明，本方案可实现与已知信号数量场景相当的分离性能。所提算法与两类已知信号数量算法相比具有竞争力，且具有高可解释性与可扩展性，在该框架下达到当前最优水平。