Energy Difference Based Speech Segregation for Close-Talk System

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.