Articulatory Modeling for Pronunciation Error Detection without Non-Native Training Data Based on DNN Transfer Learning

Abstract

Aiming at detecting pronunciation errors produced by second language learners and providing corrective feedbacks related with articulation, we address effective articulatory models based on deep neural network (DNN). Articulatory attributes are defined for manner and place of articulation. In order to efficiently train these models of non-native speech… (More)

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