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Feature selection is a crucial step in the development of a system for identifying emotions in speech. Recently, the interaction between features generated from the same audio source was rarely considered, which may produce redundant features and increase the computational costs. To solve this problem, feature selection method based on correlation analysis and Fisher is proposed, which can remove...
A facial expression recognition method based on Extreme Learning Machine (ELM) is proposed, in which Gabor filter and two dimension principal components analysis (2DPCA) are used for the feature extraction. The proposal uses ELM as the learning algorithm because of its less stringent optimization constraints for learning than other algorithms such as SVM. The experiments of facial expression recognition...
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