A minimum-mean-square-error noise reduction algorithm on Mel-frequency cepstra for robust speech recognition

@article{Yu2008AMN,
  title={A minimum-mean-square-error noise reduction algorithm on Mel-frequency cepstra for robust speech recognition},
  author={Dong Yu and Li Deng and Jasha Droppo and Jian Wu and Yifan Gong and Alex Acero},
  journal={2008 IEEE International Conference on Acoustics, Speech and Signal Processing},
  year={2008},
  pages={4041-4044}
}
We present a non-linear feature-domain noise reduction algorithm based on the minimum mean square error (MMSE) criterion on Mel-frequency cepstra (MFCC) for environment-robust speech recognition. Distinguishing from the MMSE enhancement in log spectral amplitude proposed by Ephraim and Malah (E&M) (1985), the new algorithm presented in this paper develops the suppression rule that applies to power spectral magnitude of the filter-banks' outputs and to MFCC directly, making it demonstrably more… CONTINUE READING
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