N2 - Despite various speech enhancement techniques have been developed for different applications, existing methods are limited in noisy environments with high ambient noise levels. Speech presence probability (SPP) estimation is a speech enhancement technique to reduce speech distortions, especially in low signalto-noise ratios (SNRs) scenario. In this paper, we propose a new two-dimensional (2D) Teager-energyoperators (TEOs) improved SPP estimator for speech enhancement in time-frequency (T-F) domain. Wavelet packet transform (WPT) as a multiband decomposition technique is used to concentrate the energy distribution of speech components. A minimum mean-square error (MMSE) estimator is obtained based on the generalized gamma distribution speech model in WPT domain. In addition, the speech samples corrupted by environment and occupational noises (i.e., machine shop, factory and station) at different input SNRs are used to validate the proposed algorithm. Results suggest that the proposed method achieves a significant enhancement on perceptual quality, compared with four conventional speech enhancement algorithms (i.e., MMSE-84, MMSE-04, Wiener-96, and BTW). L1 - http://www.journals.pan.pl/Content/102720/PDF/aoa-2016-0056.pdf L2 - http://www.journals.pan.pl/Content/102720 PY - 2016 IS - No 3 EP - 590 DO - 10.1515/aoa-2016-0056 KW - speech enhancement KW - speech presence probability KW - wavelet packet transform KW - two-dimensional Teager energy operator A1 - Sun, Pengfei A1 - Qin, Jun PB - Polish Academy of Sciences, Institute of Fundamental Technological Research, Committee on Acoustics VL - vol. 41 DA - 2016 T1 - Wavelet Packet Transform based Speech Enhancement via Two-Dimensional SPP Estimator with Generalized Gamma Priors SP - 579 UR - http://www.journals.pan.pl/dlibra/publication/edition/102720 T2 - Archives of Acoustics