Isolated word recognition using decision tree classifiers and ti

Details Isolated word recognition using decision tree classifiers and ti Isolated word recognition using decision tree classifiers and ti

1995-10-31

1997-08-12

MacDonald, Allen R.

395 241, 395 243, 395 245, 395 247, 395 249, G10L 506

Patent

active

056574240

ABSTRACT:
Machine recognition of isolated word utterances is carried out by applying time-indexed feature vectors to binary decision tree classifiers. A respective classifier is provided for each target word in the vocabulary of words to be recognized. Determinants for the nodes in the classifier tree structure are formed, during a training process, as hyper-planes which perform a "mean split" between the centroids of target word and non-target word classes of feature vectors assigned to the respective nodes. The process of training the machine recognition system is facilitated by storing node-assignment data in association with training data vectors. The assignment of training data vectors to sub-nodes proceeds on a level-by-level basis in the tree structure.

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