Noisy training for deep neural networks in speech recognition

@article{Yin2015NoisyTF,
  title={Noisy training for deep neural networks in speech recognition},
  author={Shi Yin and Chao Liu and Zhiyong Zhang and Yiye Lin and Dong Wang and Javier Tejedor and Thomas Fang Zheng and Yinguo Li},
  journal={EURASIP J. Audio, Speech and Music Processing},
  year={2015},
  volume={2015},
  pages={2}
}
Deep neural networks (DNNs) have gained remarkable success in speech recognition, partially attributed to the flexibility of DNN models in learning complex patterns of speech signals. This flexibility, however, may lead to serious over-fitting and hence miserable performance degradation in adverse acoustic conditions such as those with high ambient noises. We propose a noisy training approach to tackle this problem: by injecting moderate noises into the training data intentionally and randomly… CONTINUE READING
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