Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Research Article Improved Reproduction of Stops in Noise Reduction Systems with Adaptive Windows and Nonstationarity Detection | Hindawi Publishing Corporation EURASIP Journal on Advances in Signal Processing Volume 2009 Article ID 469480 17 pages doi 2009 469480 Research Article Improved Reproduction of Stops in Noise Reduction Systems with Adaptive Windows and Nonstationarity Detection Dirk Mauler and Rainer Martin EURASIP Member Department of Electrical Engineering and Information Sciences Ruhr-Universitat Bochum 44801 Bochum Germany Correspondence should be addressed to Dirk Mauler Received 12 December 2008 Accepted 17 March 2009 Recommended by Sven Nordholm A new block-based noise reduction system is proposed which focuses on the preservation of transient sounds like stops or speech onsets. The power level of consonants has been shown to be important for speech intelligibility. In single-channel noise reduction systems however these sounds are frequently severely attenuated. The main reasons for this are an insufficient temporal resolution of transient sounds and a delayed tracking of important control parameters. The key idea of the proposed system is the detection of non-stationary input data. Depending on that decision a pair of spectral analysis-synthesis windows is selected which either provides high temporal or high spectral resolution. Furthermore the decision-directed approach for the estimation of the a priori SNR is modified so that speech onsets are tracked more quickly without sacrificing performance in stationary signal regions. The proposed solution shows significant improvements in the preservation of stops with an overall system delay input-output excluding group delay of noise reduction filter of only 10 milliseconds. Copyright 2009 D. Mauler and R. Martin. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. 1. Introduction A large class of speech enhancement algorithms is realized in .
