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- W4473315 abstract "Phonetic decision trees are a key concept in acoustic modeling for large vocabulary continuous speech recognition. Although discriminative training has become a major line of research in speech recognition and all state-of-the-art acoustic models are trained discriminatively, the conventional phonetic decision tree approach still relies on the maximum likelihood principle. In this paper we develop a splitting criterion based on the minimization of the classification error. An improvement of more than 10% relative over a discriminatively trained baseline system on the Wall Street Journal corpus suggests that the proposed approach is promising. Index Terms: discriminative training, phonetic decision trees, state tying, new paradigms" @default.
- W4473315 created "2016-06-24" @default.
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- W4473315 date "2010-09-26" @default.
- W4473315 modified "2023-09-26" @default.
- W4473315 title "A discriminative splitting criterion for phonetic decision trees" @default.
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- W4473315 doi "https://doi.org/10.21437/interspeech.2010-10" @default.
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