Adaptation in Statistical Pattern Recognition Using Tangent Vectors
Abstract
We integrate the tangent method into a statistical framework for classification
analytically and practically. The resulting consistent framework for adaptation allows us to
efficiently estimate the tangent vectors representing the variability. The framework improves
classification results on two real-world pattern recognition tasks from the domains
handwritten character recognition and automatic speech recognition.
analytically and practically. The resulting consistent framework for adaptation allows us to
efficiently estimate the tangent vectors representing the variability. The framework improves
classification results on two real-world pattern recognition tasks from the domains
handwritten character recognition and automatic speech recognition.
