TWO-CHANNEL POST-FILTERING BASED ON ADAPTIVE SMOOTHING AND NOISE PROPERTIES
Industrial Technology for Speech Processing Applications
Presented by: Chengshi Zheng, Author(s): Chengshi Zheng, Yi Zhou, Xiaohu Hu, Xiaodong Li, Institute of Acoustics Chinese Academy of Sciences, China
This paper studies the statistical properties of the gain functions, which are often used for two-channel post filtering (TC-PF) algorithms. We reveal that the smoothing factor has a significant impact on both noise reduction and musical noise. When the smoothing factor increases, noise reduction can be improved and musical noise can be reduced simultaneously. However, the smoothing factor could not be too close to one because the system can only be assumed to be timeinvariant for short durations. To solve this problem, this paper proposes an adaptive smoothing scheme by detecting the sudden change of the system. Moreover, the residual noise floor is adaptively chosen based on the structure of the noise power spectral density (NPSD) to further suppress the tonal noise components. Experimental results show the better performance of the proposed algorithm in terms of the segmental signalto-noise-ratio (SNR) and the PESQ improvements.