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This paper presents a minimum generation error (MGE) training method for hidden Markov model (HMM) based prediction of articulatory movements when both text and audio inputs are given. In this method, MGE criterion is adopted to replace the maximum likelihood (ML) criterion to estimate model parameters for the unified acoustic-articulatory HMMs. Different from the MGE training for HMM-based acoustic...
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