This paper explains the conception of auditory scene analysis (ASA) and its effect in speech signals processing. We propose a method about separation of overlapping speech signals using wavelet transform based on auditory scene analysis in this paper.
本文简述了声场景分析(ASA)的概念及其在语音信号处理中的作用，并以小波变换的分析方法为工具，提出一种基于声场景分析的混叠语音信号分离算法。
参考来源 - 基于声场景分析的混叠语音信号分离·2,447,543篇论文数据，部分数据来源于NoteExpress
以上来源于: WordNet
Above mentioned method could be applied to computational auditory scene analysis.
本文提出的方法可应用于计算声场景分析中。
The most two popular algorithms are Computational Auditory Scene Analysis (CASA) and Blind Source Separation.
目前常用的语音分离方法主要有听觉场景分析法和盲信号分离法。
Perception: Visual Scene Analysis, Object Recognition, Auditory Scene Analysis, Depth Perception, Stereo Vision, Stereograms.
知觉：视觉景象分析、物体辨识、听觉景象分析、深度知觉、立体视觉、立体图。
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