Parametric Resynthesis With Neural Vocoders

@article{Maiti2019ParametricRW,
  title={Parametric Resynthesis With Neural Vocoders},
  author={Soumi Maiti and Michael I. Mandel},
  journal={2019 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA)},
  year={2019},
  pages={303-307}
}
  • Soumi Maiti, Michael I. Mandel
  • Published 16 June 2019
  • Computer Science
  • 2019 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA)
Noise suppression systems generally produce output speech with compromised quality. We propose to utilize the high quality speech generation capability of neural vocoders for noise suppression. We use a neural network to predict clean mel-spectrogram features from noisy speech and then compare two neural vocoders, WaveNet and WaveGlow, for synthesizing clean speech from the predicted mel spectrogram. Both WaveNet and WaveGlow achieve better subjective and objective quality scores than the… 

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