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báo cáo hóa học:" Research Article Musical Sound Separation Based on Binary Time-Frequency Masking"

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 Musical Sound Separation Based on Binary Time-Frequency Masking | Hindawi Publishing Corporation EURASIP Journal on Audio Speech and Music Processing Volume 2009 Article ID 130567 10 pages doi 10.1155 2009 130567 Research Article Musical Sound Separation Based on Binary Time-Frequency Masking Yipeng Li1 and DeLiang Wang2 1 Department of Computer Science and Engineering The Ohio State University Columbus OH 43210-1277 USA 2 Department of Computer Science and Engineering and Center of Cognitive Science The Ohio State University Columbus OH 43210-1277 USA Correspondence should be addressed to Yipeng Li li.434@osu.edu Received 15 November 2008 Revised 20 March 2009 Accepted 16 April 2009 Recommended by Q.-J. Fu The problem of overlapping harmonics is particularly acute in musical sound separation and has not been addressed adequately. We propose a monaural system based on binary time-frequency masking with an emphasis on robust decisions in timefrequency regions where harmonics from different sources overlap. Our computational auditory scene analysis system exploits the observation that sounds from the same source tend to have similar spectral envelopes. Quantitative results show that utilizing spectral similarity helps binary decision making in overlapped time-frequency regions and significantly improves separation performance. Copyright 2009 Y. Li and D. Wang. 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 Monaural musical sound separation has received significant attention recently. Analyzing a musical signal is difficult in general due to the polyphonic nature of music but extracting useful information from monophonic music is considerably easier. Therefore a musical sound separation system would be a very useful processing step for many audio applications such as automatic music transcription automatic instrument identification music information .