The a Priori SNR Estimator Based on Cepstral Processing

Wang J, Yang G, Liu J, Peng R. The a Priori SNR Estimator Based on Cepstral Processing. In: AES Convention 141. Audio Engineering Society; 2016. Paper 9645. Available from: https://aes.org/publications/elibrary-page/?id=18449

@inproceedings{Wang2016_18449,
  author = {Wang, Jie and Yang, Guangquan and Liu, JingJing and Peng, Renhua},
  title = {{The a Priori SNR Estimator Based on Cepstral Processing}},
  booktitle = {AES Convention 141},
  note = {Paper 9645},
  year = {2016},
  month = sep,
  publisher = {Audio Engineering Society},
  url = {https://aes.org/publications/elibrary-page/?id=18449}
}

TY  - CPAPER
TI  - The a Priori SNR Estimator Based on Cepstral Processing
AU  - Wang, Jie
AU  - Yang, Guangquan
AU  - Liu, JingJing
AU  - Peng, Renhua
T2  - AES Convention 141
M1  - Paper 9645
PY  - 2016
DA  - 2016/09/06
UR  - https://aes.org/publications/elibrary-page/?id=18449
PB  - Audio Engineering Society
LA  - en
AB  - For single-channel speech enhancement systems, the a priori SNR is a key parameter for Wiener-type algorithms. The a priori SNR estimators can reduce the noise efficiently when the noise power spectral density (NPSD) can be estimated accurately. However, when the NPSD is overestimated/underestimated, the a priori SNR may lead to the speech distortion and the residual noise. To solve this problem, this paper proposes to estimate the a priori SNR based on cepstral processing, which not only can suppress harmonic speech components in the noisy speech segments, but also can reduce strong noise components in noise-only segments. Simulation results show that the proposed algorithm has better performance than the traditional DD and Plapous’s two-step algorithms.
ER  -