Joint noise adaptive training for robust automatic speech recognition

@article{Narayanan2014JointNA,
  title={Joint noise adaptive training for robust automatic speech recognition},
  author={Arun Narayanan and DeLiang Wang},
  journal={2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
  year={2014},
  pages={2504-2508}
}
We explore time-frequency masking to improve noise robust automatic speech recognition. Apart from its use as a frontend, we use it for providing smooth estimates of speech and noise which are then passed as additional features to a deep neural network (DNN) based acoustic model. Such a system improves performance on the Aurora-4 dataset by 10.5% (relative) compared to the previous best published results. By formulating separation as a supervised mask estimation problem, we develop a unified… CONTINUE READING
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