Feature space dimension reduction in speech emotion recognition using support vector machine.
Bo-Chang ChiouChia-Ping ChenPublished in: APSIPA (2013)
Keyphrases
- dimension reduction
- feature space
- support vector machine
- emotion recognition
- emotional state
- dimension reduction methods
- feature selection
- principal component analysis
- high dimensionality
- high dimensional
- feature extraction
- feature vectors
- low dimensional
- linear discriminant analysis
- kernel function
- kernel methods
- support vector machine svm
- high dimensional problems
- random projections
- audio visual
- dimensionality reduction
- k nearest neighbor
- hyperplane
- svm classifier
- manifold learning
- partial least squares
- feature set
- high dimensional data analysis
- training set
- high dimensional data
- training samples
- classification accuracy
- discriminant analysis
- input space
- data points
- sparse coding
- input data
- facial expressions
- knn
- lower dimensional
- kernel pca
- object recognition
- machine learning
- data sets