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 Denoising in the Domain of Spectrotemporal Modulations | Hindawi Publishing Corporation EURASIP Journal on Audio Speech and Music Processing Volume 2007 Article ID 42357 8 pages doi 2007 42357 Research Article Denoising in the Domain of Spectrotemporal Modulations Nima Mesgarani and Shihab Shamma Electrical Engineering Department University of Maryland 1103 Building College Park MD 20742 USA Received 19 December 2006 Revised 7 May 2007 Accepted 10 September 2007 Recommended by Wai-Yip Geoffrey Chan A noise suppression algorithm is proposed based on filtering the spectrotemporal modulations of noisy signals. The modulations are estimated from a multiscale representation of the signal spectrogram generated by a model of sound processing in the auditory system. A significant advantage of this method is its ability to suppress noise that has distinctive modulation patterns despite being spectrally overlapping with the signal. The performance of the algorithm is evaluated using subjective and objective tests with contaminated speech signals and compared to traditional Wiener filtering method. The results demonstrate the efficacy of the spectrotemporal filtering approach in the conditions examined. Copyright 2007 N. Mesgarani and S. Shamma. 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. Noise suppression with complex broadband signals is often employed in order to enhance quality or intelligibility in a wide range of applications including mobile communication hearing aids and speech recognition. In speech research this has been an active area of research for over fifty years mostly framed as a statistical estimation problem in which the goal is to estimate speech from its sum with other independent processes noise . This approach requires an underlying statistical model of the signal and noise as well as an optimization criterion. In some of .
