Arnon Amir, Michael Lindenbaum
IEEE Transactions on Pattern Analysis and Machine Intelligence
A supervised classifier is described where a systematic search through a training database produced an efficacious set of prototypes for its operation. Using this technique, two studies, one dealing with phone recognition and another with large-vocabulary speech recognition, were conducted with data from several speakers. The superiority of the supervised classifier design is demonstrated by comparative performance analysis. © 1994 IEEE
Arnon Amir, Michael Lindenbaum
IEEE Transactions on Pattern Analysis and Machine Intelligence
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