Using Laplacian eigenmaps latent variable model and manifold learning to improve speech recognition accuracy.
Ayyoob JafariFarshad AlmasganjPublished in: Speech Commun. (2010)
Keyphrases
- manifold learning
- laplacian eigenmaps
- recognition accuracy
- nonlinear dimensionality reduction
- latent space
- low dimensional
- face recognition
- dimensionality reduction
- semi supervised
- kernel pca
- dimension reduction
- high dimensional data
- feature extraction
- locally linear embedding
- sparse representation
- high dimensional
- graph laplacian
- manifold structure
- feature space
- pattern recognition
- machine learning