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1d-convolution

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TF-1D-2D-ResNetV1-2-SEResNet-ResNeXt-SEResNeXt

Models supported: ResNet, ResNetV2, SE-ResNet, ResNeXt, SE-ResNeXt [layers: 18, 34, 50, 101, 152] (1D and 2D versions with DEMO for Classification and Regression).

  • Updated Jan 27, 2022
  • Jupyter Notebook

In this work we propose two postprocessing approaches applying convolutional neural networks (CNNs) either in the time domain or the cepstral domain to enhance the coded speech without any modification of the codecs. The time domain approach follows an end-to-end fashion, while the cepstral domain approach uses analysis-synthesis with cepstral d…

  • Updated Mar 8, 2020
  • Python

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