Post-Processing for the Mask of Computational Auditory Scene Analysis in Monaural Speech Segregation

2018 ◽  
Vol 21 (4) ◽  
Author(s):  
Wen-Hsing Lai ◽  
Cheng-Jia Yang ◽  
Siou-Lin Wang
Keyword(s):  
Auditory Scene Analysis ◽  
Scene Analysis ◽  
Post Processing ◽  
Computational Auditory Scene Analysis ◽  
Speech Segregation ◽  
Auditory Scene

Energy Difference Based Speech Segregation for Close-Talk System

2012 ◽  
Vol 229-231 ◽  
pp. 1738-1741 ◽  
Author(s):  
Hong Zhou ◽  
Yi Jiang ◽  
Ming Jiang ◽  
Qiang Chen
Keyword(s):  
Energy Difference ◽  
Auditory Scene Analysis ◽  
Scene Analysis ◽  
Computational Auditory Scene Analysis ◽  
Clustering Method ◽  
Separation Algorithm ◽  
Time Frequency ◽  
Speech Segregation ◽  
Auditory Scene ◽  
Novel Algorithm

Within the framework of computational auditory scene analysis (CASA), a speech separation algorithm based on energy difference for close-talk system was proposed. The two microphones received the mixture signal of close target speech and far noise sound at the same time. The inter-microphone intensity differences (IMID) of the two microphones in time-frequency (T-F) units were calculated. And used as cues to generate the binary masks with the K-means two class clustering method. Experiments indicated that this novel algorithm could separate the target speech from the mixture sound, and performed well in a big noise environment.

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