An introduction to support Vector Machines: and other kernel-based learning methods
An introduction to support Vector Machines: and other kernel-based learning methods
A Nonlinearized Discriminant Analysis and Its Application to Speech Impediment Therapy
TSD '01 Proceedings of the 4th International Conference on Text, Speech and Dialogue
Speaker normalization via springy discriminant analysis and pitch estimation
TSD'07 Proceedings of the 10th international conference on Text, speech and dialogue
On kernel discriminant analyses applied to phoneme classification
ISNN'05 Proceedings of the Second international conference on Advances in neural networks - Volume Part II
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Making use of the ubiquitous kernel notion, we present a new nonlinear supervised feature extraction technique called Kernel Springy Discriminant Analysis. We demonstrate that this method can efficiently reduce the number of features and increase classification performance. The improvements obtained admittedly arise from the nonlinear nature of the extraction technique developed here. Since phonological awareness is a great importance in learning to read, a computer-aided training system could be most beneficial in teaching young learners. Naturally, our system employs an effective automatic phoneme recognizer based on the proposed feature extraction technique.