Detecting Mispronunciations of L2 Learners and Providing Corrective Feedback Using Knowledge-Guided and Data-Driven Decision Trees

@inproceedings{Li2016DetectingMO,
  title={Detecting Mispronunciations of L2 Learners and Providing Corrective Feedback Using Knowledge-Guided and Data-Driven Decision Trees},
  author={Wei Li and Kehuang Li and Sabato Marco Siniscalchi and Nancy F. Chen and Chin-Hui Lee},
  booktitle={INTERSPEECH},
  year={2016}
}
We propose a novel decision tree based framework to detect phonetic mispronunciations produced by L2 learners caused by using inaccurate speech attributes, such as manner and place of articulation. Compared with conventional score-based CAPT (computer assisted pronunciation training) systems, our proposed framework has three advantages: (1) each mispronunciation in a tree can be interpreted and communicated to the L2 learners by traversing the corresponding path from a leaf node to the root… 

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