tailieunhanh - Báo cáo toán học: " Transient noise reduction in speech signal with a modified long-term predictor"

Tuyển tập các báo cáo nghiên cứu khoa học ngành toán học được đăng trên tạp chí toán học quốc tế đề tài: Transient noise reduction in speech signal with a modified long-term predictor | Choi and Kang EURASIP Journal on Advances in Signal Processing 2011 2011 141 http content 2011 1 141 o EURASIP Journal on Advances in Signal Processing a SpringerOpen Journal RESEARCH Open Access Transient noise reduction in speech signal with a modified long-term predictor Min-Seok Choi and Hong-Goo Kang Abstract This article proposes an efficient median filter based algorithm to remove transient noise in a speech signal. The proposed algorithm adopts a modified long-term predictor LTP as the pre-processor of the noise reduction process to reduce speech distortion caused by the nonlinear nature of the median filter. This article shows that the LTP analysis does not modify to the characteristic of transient noise during the speech modeling process. Oppositely if a short-term linear prediction STP filter is employed as a pre-processor the enhanced output includes residual noise because the STP analysis and synthesis process keeps and restores transient noise components. To minimize residual noise and speech distortion after the transient noise reduction a modified LTP method is proposed which estimates the characteristic of speech more accurately. By ignoring transient noise presence regions in the pitch lag detection step the modified LTP successfully avoids being affected by transient noise. A backward pitch prediction algorithm is also adopted to reduce speech distortion in the onset regions. Experimental results verify that the proposed system efficiently eliminates transient noise while preserving desired speech signal. Keywords speech enhancement transient noise reduction long-term prediction median filter 1 Introduction Reducing noise from noise-corrupted speech is essential for communication or recording devices. Spectral subtractive noise reduction algorithms have been widely developed under the assumption that input noise is stationary or slowly varying 1-3 . Therefore the linear filtering methods cannot remove transient noise .