Speech enhancement based on deep denoising autoencoder

@inproceedings{Lu2013SpeechEB,
  title={Speech enhancement based on deep denoising autoencoder},
  author={Xugang Lu and Yu Tsao and Shigeki Matsuda and Chiori Hori},
  booktitle={INTERSPEECH},
  year={2013}
}
We previously have applied deep autoencoder (DAE) for noise reduction and speech enhancement. However, the DAE was trained using only clean speech. In this study, by using noisyclean training pairs, we further introduce a denoising process in learning the DAE. In training the DAE, we still adopt greedy layer-wised pretraining plus fine tuning strategy. In pretraining, each layer is trained as a one-hidden-layer neural autoencoder (AE) using noisy-clean speech pairs as input and output (or… CONTINUE READING

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