Adversarial Multi-Task Learning of Deep Neural Networks for Robust Speech Recognition

@inproceedings{Shinohara2016AdversarialML,
  title={Adversarial Multi-Task Learning of Deep Neural Networks for Robust Speech Recognition},
  author={Yusuke Shinohara},
  booktitle={INTERSPEECH},
  year={2016}
}
A method of learning deep neural networks (DNNs) for noise robust speech recognition is proposed. It is widely known that representations (activations) of well-trained DNNs are highly invariant to noise, especially in higher layers, and such invariance leads to the noise robustness of DNNs. However, little is known about how to enhance such invariance of representations, which is a key for improving robustness. In this paper, we propose adversarial multi-task learning of DNNs for explicitly… CONTINUE READING
Highly Cited
This paper has 33 citations. REVIEW CITATIONS

2 Figures & Tables

Topics

Statistics

02040201620172018
Citations per Year

Citation Velocity: 14

Averaging 14 citations per year over the last 3 years.

Learn more about how we calculate this metric in our FAQ.