Ensemble Methods for Phoneme Classification
نویسندگان
چکیده
This paper investigates a number of ensemble methods for improving the performance of phoneme classification for use in a speech recognition system. Two ensemble methods are described; boosting and mixtures of experts, both in isolation and in combination. Results are presented on two speech recognition databases: an isolated word database and a large vocabulary continuous speech database. These results show that principled ensemble methods such as boosting and mixtures provide superior performance to more naive ensemble methods such as averaging .
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