In this paper,we applied RobustICA to speech separation and made a comprehensive comparison to FastICA according to the separation results.Through a series of speech signal separation test,RobustICA reduced the separa...In this paper,we applied RobustICA to speech separation and made a comprehensive comparison to FastICA according to the separation results.Through a series of speech signal separation test,RobustICA reduced the separation time consumed by FastICA with higher stability,and speeches separated by RobustICA were proved to having lower separation errors.In the 14 groups of speech separation tests,separation time consumed by RobustICA was 3.185 s less than FastICA by nearly 68%.Separation errors of FastICA had a float between 0.004 and 0.02,while the errors of RobustICA remained around 0.003.Furthermore,compared to FastICA,RobustICA showed better separation robustness.Experimental results showed that RobustICA was successful to apply to the speech signal separation,and showed superiority to FastICA in speech separation.展开更多
基金National Natural Science Foundation of Chinagrant number:61271082,61201029,61102094
文摘In this paper,we applied RobustICA to speech separation and made a comprehensive comparison to FastICA according to the separation results.Through a series of speech signal separation test,RobustICA reduced the separation time consumed by FastICA with higher stability,and speeches separated by RobustICA were proved to having lower separation errors.In the 14 groups of speech separation tests,separation time consumed by RobustICA was 3.185 s less than FastICA by nearly 68%.Separation errors of FastICA had a float between 0.004 and 0.02,while the errors of RobustICA remained around 0.003.Furthermore,compared to FastICA,RobustICA showed better separation robustness.Experimental results showed that RobustICA was successful to apply to the speech signal separation,and showed superiority to FastICA in speech separation.
