Semi-supervised DNN training in meeting recognition

@article{Zhang2014SemisupervisedDT,
  title={Semi-supervised DNN training in meeting recognition},
  author={Pengyuan Zhang and Yulan Liu and Thomas Hain},
  journal={2014 IEEE Spoken Language Technology Workshop (SLT)},
  year={2014},
  pages={141-146}
}
Training acoustic models for ASR requires large amounts of labelled data which is costly to obtain. Hence it is desirable to make use of unlabelled data. While unsupervised training can give gains for standard HMM training, it is more difficult to make use of unlabelled data for discriminative models. This paper explores semi-supervised training of Deep Neural Networks (DNN) in a meeting recognition task. We first analyse the impact of imperfect transcription on the DNN and the ASR performance… CONTINUE READING
Highly Cited
This paper has 19 citations. REVIEW CITATIONS
15 Citations
12 References
Similar Papers

Citations

Publications citing this paper.
Showing 1-10 of 15 extracted citations

References

Publications referenced by this paper.
Showing 1-10 of 12 references

Similar Papers

Loading similar papers…