Two class-separability criteria based on the divergence measure are proposed to improve speech recognition performance. The average and weighted average divergence measures are used as criteria for finding a transformation matrix which maps the original features into a more discriminative subspace. Results are presented for a highly confusable task.
ASJC Scopus subject areas
- Acoustics and Ultrasonics
- Computer Vision and Pattern Recognition
- Electrical and Electronic Engineering