Automatic assessment of English learner pronunciation using discriminative classifiers

@article{Nicolao2015AutomaticAO,
  title={Automatic assessment of English learner pronunciation using discriminative classifiers},
  author={Mauro Nicolao and Amy V. Beeston and Thomas Hain},
  journal={2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
  year={2015},
  pages={5351-5355}
}
This paper presents a novel system for automatic assessment of pronunciation quality of English learner speech, based on deep neural network (DNN) features and phoneme specific discriminative classifiers. DNNs trained on a large corpus of native and non-native learner speech are used to extract phoneme posterior probabilities. A part of the corpus includes per phone teacher annotations, which allows training of two Gaussian Mixture Models (GMM), representing correct pronunciations and typical… CONTINUE READING

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