Wavelet Transform Using Neyman-Pearson Criterion in Speech Recognition

@article{Liu2008WaveletTU,
  title={Wavelet Transform Using Neyman-Pearson Criterion in Speech Recognition},
  author={Xuefei Liu and Zhiying Wu and Jia Lei Qin and Fang Zhang and Wenjun Song},
  journal={2008 Second International Symposium on Intelligent Information Technology Application},
  year={2008},
  volume={3},
  pages={80-83}
}
To obtain a high robust of speech recognition for noisy conditions, a new pre-processing stage based on wavelet thresholding algorithm is proposed in this paper. The purpose of using the DWT is to benefit from its localization property in the time and frequency domains. Compromise function is proposed compared with hard and soft thresholding function. A new thresholding value, Neyman-Pearson criterion is proposed compared with the commonly used Sqtwolog, Rigrsure, minimaxi criterion. MSE and… CONTINUE READING

Similar Papers

Citations

Publications citing this paper.
SHOWING 1-2 OF 2 CITATIONS

References

Publications referenced by this paper.
SHOWING 1-6 OF 6 REFERENCES

“ Denoising by soft - thresholding ”

Gang Wang, Yaohua Xu
  • IEEE Trans . Inf . Theoryl
  • 2008

Noise compensation for speech recognition with arbitrary additive noise

  • IEEE Transactions on Audio, Speech, and Language Processing
  • 2006

Speech Recognition for Noisy Conditions Based on Discrete Wavelet Transform and Parallel Model Combination, “icemi’200”5

Hu Chuihai, Liu Xuefei
  • 2005
VIEW 1 EXCERPT

A Vavelet-based Voice Activity Detection Algorithm in Noisy Environments

Shi Huang Chen, Jhing-Fa Wang
  • Journal of Southeastcon
  • 2002
VIEW 1 EXCERPT

Feature extraction using discrete wavelet transform for speech recognition

  • Proceedings of the IEEE SoutheastCon 2000. 'Preparing for The New Millennium' (Cat. No.00CH37105)
  • 2000
VIEW 1 EXCERPT