Discriminative training of Gaussian mixture bigram models with application to Chinese dialect identification


This study focuses on the parametric stochastic modeling of characteristic sound features that distinguish languages from one another. A new stochastic model, the so-called Gaussian mixture bigram model (GMBM), that allows exploitation of the acoustic feature bigram statistics without requiring transcribed training data is introduced. For greater efficiency… (More)
DOI: 10.1016/S0167-6393(00)00090-X


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