A Signal Subspace Speech Enhancement Approach Based on Joint Low-Rank and Sparse Matrix Decomposition

@inproceedings{Sun2016ASS,
  title={A Signal Subspace Speech Enhancement Approach Based on Joint Low-Rank and Sparse Matrix Decomposition},
  author={Chengli Sun and Jianxiao Xie and Yan Leng},
  year={2016}
}
Subspace-based methods have been effectively used to estimate enhanced speech from noisy speech samples. In the traditional subspace approaches, a critical step is splitting of two invariant subspaces associated with signal and noise via subspace decomposition, which is often performed by singular-value decomposition or eigenvalue decomposition. However, these decomposition algorithms are highly sensitive to the presence of large corruptions, resulting in a large amount of residual noise within… CONTINUE READING

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Subspace Approach for Enhancing Speech based on SVD.

  • 2018 International Conference on Communications and Electrical Engineering (ICCEE)
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