What do neural networks listen to? Exploring the crucial bands in Speech Enhancement using Sinc-convolution
ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)(2024)
摘要
This study introduces a reformed Sinc-convolution (Sincconv) framework
tailored for the encoder component of deep networks for speech enhancement
(SE). The reformed Sincconv, based on parametrized sinc functions as band-pass
filters, offers notable advantages in terms of training efficiency, filter
diversity, and interpretability. The reformed Sinc-conv is evaluated in
conjunction with various SE models, showcasing its ability to boost SE
performance. Furthermore, the reformed Sincconv provides valuable insights into
the specific frequency components that are prioritized in an SE scenario. This
opens up a new direction of SE research and improving our knowledge of their
operating dynamics.
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关键词
Speech Ehancement,Sinc-convolution,Interpretability
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