Pronunciation error detection using DNN articulatory model based on multi-lingual and multi-task learning

@article{Duan2016PronunciationED,
  title={Pronunciation error detection using DNN articulatory model based on multi-lingual and multi-task learning},
  author={Richeng Duan and Tatsuya Kawahara and Masatake Dantsuji and Jinsong Zhang},
  journal={2016 10th International Symposium on Chinese Spoken Language Processing (ISCSLP)},
  year={2016},
  pages={1-5}
}
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 without using such data, which is difficult to collect in a large scale, we propose a multi-lingual learning method, in which the speech… CONTINUE READING

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