The Structure of Noise Power Spectral Density-Driven Adaptive Post-Filtering Algorithm

Wang J, Zheng C, Zhang C, Sun Y. The Structure of Noise Power Spectral Density-Driven Adaptive Post-Filtering Algorithm. In: AES Convention 135. Audio Engineering Society; 2013. Paper 8943. Available from: https://aes.org/publications/elibrary-page/?id=16993

@inproceedings{Wang2013_16993,
  author = {Wang, Jie and Zheng, Chengshi and Zhang, Chunliang and Sun, Yueyan},
  title = {{The Structure of Noise Power Spectral Density-Driven Adaptive Post-Filtering Algorithm}},
  booktitle = {AES Convention 135},
  note = {Paper 8943},
  year = {2013},
  month = oct,
  publisher = {Audio Engineering Society},
  url = {https://aes.org/publications/elibrary-page/?id=16993}
}

TY  - CPAPER
TI  - The Structure of Noise Power Spectral Density-Driven Adaptive Post-Filtering Algorithm
AU  - Wang, Jie
AU  - Zheng, Chengshi
AU  - Zhang, Chunliang
AU  - Sun, Yueyan
T2  - AES Convention 135
M1  - Paper 8943
PY  - 2013
DA  - 2013/10/06
UR  - https://aes.org/publications/elibrary-page/?id=16993
PB  - Audio Engineering Society
LA  - en
AB  - Conventional post-filtering (CPF) algorithms often use a fixed filter bandwidth to estimate the auto-spectra and the cross-spectrum. This paper first studies the drawback of the CPF algorithms under the stochastic model and discusses the ways to improve the performances of the CPF algorithms. To improve noise reduction without introducing audible speech distortion, we propose a novel spectral estimator, which is based on the structure of the noise power spectral density (NPSD). The proposed spectral estimator is applied to improve the performance of the CPF. Experimental results verify that the proposed algorithm is better than the CPF algorithms in terms of the segmental signal-to-noise-ratio improvement and the noise reduction, especially the noise reduction, is about 6 dB higher than the CPF.
ER  -