Humans have the ability to easily separate a composed speech and to form perceptual representations of the constituent sources in an acoustic mixture thanks to their ears. Until recently, researchers attempt to build computer models of high-level functions of the auditory system. The problem of the composed speech segregation is still a very challenging problem for these researchers. In our case, we are interested in approaches that are addressed to the monaural speech segregation. For this purpose, we study in this paper the computational auditory scene analysis (CASA) to segregate speech from monaural mixtures. CASA is the reproduction of the source organization achieved by listeners. It is based on two main stages: segmentation and grouping. In this work, we have presented, and compared several studies that have used CASA for speech separation and recognition.

中文翻译：

---

几种用于单声道语音隔离的计算听觉场景分析（CASA）技术的比较。

人类的耳朵能够轻松地分离出所组成的语音，并在声音混合物中形成组成源的感性表示。直到最近，研究人员仍试图建立听觉系统高级功能的计算机模型。对于这些研究人员来说，语音分离的问题仍然是一个非常具有挑战性的问题。在我们的案例中，我们对解决单声道语音隔离的方法很感兴趣。为此，我们在本文中研究了计算听觉场景分析（CASA），以将语音与单声道混合物分离开来。CASA是听众所实现的源组织的复制品。它基于两个主要阶段：分段和分组。在这项工作中，我们提出了