Speech enhancement based on robust NMF solved by alternating direction method of multipliers

@article{Li2015SpeechEB,
  title={Speech enhancement based on robust NMF solved by alternating direction method of multipliers},
  author={Yinan Li and Xiongwei Zhang and Meng Sun and Jingfeng Pan},
  journal={2015 IEEE 17th International Workshop on Multimedia Signal Processing (MMSP)},
  year={2015},
  pages={1-5}
}
A robust version of non-negative matrix factorization (RNMF) with generalized Kullback-Leibler divergence designed for the task of unsupervised monaural speech enhancement is proposed. RNMF tackles unsupervised speech enhancement problem through factorizing the magnitude spectrum of mixture into the sum of a non-negative sparse matrix and a non-negative low-rank matrix. The parameters of nonnegative components are estimated through minimizing the reconstruction error defined by the divergence… CONTINUE READING

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