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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 Real-Time Recognition of Percussive Sounds by a Model-Based Method | Hindawi Publishing Corporation EURASIP Journal on Advances in Signal Processing Volume 2011 Article ID 291860 14 pages doi 10.1155 2011 291860 Research Article Real-Time Recognition of Percussive Sounds by a Model-Based Method Umut Simsekli 1 Antti Jylha 2 Cumhur Erkut 2 and A. Taylan Cemgil1 1 Department of Computer Engineering Bogazici University Bebek 34342 Istanbul Turkey 2 Department of Signal Processing and Acoustics Aalto University School of Science and Technology P.O. Box 13000 00076Aalto Finland Correspondence should be addressed to Antti Jylha antti.jylha@tkk.fi Received 22 September 2010 Accepted 26 November 2010 Academic Editor Victor Lazzarini Copyright 2011 Umut Simsekli et al. 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. Interactive musical systems require real-time low-latency accurate and reliable event detection and classification algorithms. In this paper we introduce a model-based algorithm for detection of percussive events and test the algorithm on the detection and classification of different percussive sounds. We focus on tuning the algorithm for a good compromise between temporal precision classification accuracy and low latency. The model is trained offline on different percussive sounds using the expectation maximization approach for learning spectral templates for each sound and is able to run online to detect and classify sounds from audio stream input by a Hidden Markov Model. Our results indicate that the approach is promising and applicable in design and development of interactive musical systems. 1. Introduction Percussion instruments traditionally provide the rhythmic backbone in music. In the past few years their automatic detection and classification has been studied in the context of music information retrieval for numerous purposes including metrical analysis .
