Báo cáo hóa học: " Research Article Tracking Intermittently Speaking Multiple Speakers Using a Particle Filter"

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 Tracking Intermittently Speaking Multiple Speakers Using a Particle Filter | Hindawi Publishing Corporation EURASIP Journal on Audio Speech and Music Processing Volume 2009 Article ID 673202 11 pages doi 2009 673202 Research Article Tracking Intermittently Speaking Multiple Speakers Using a Particle Filter Angela Quinlan Mitsuru Kawamoto EURASIP Member Yosuke Matsusaka Hideki Asoh and Futoshi Asano Central 2 1-1-1 Umezono Tsukuba Ibaraki 305-8568 Japan Correspondence should be addressed to Mitsuru Kawamoto Received 10 August 2008 Revised 5 March 2009 Accepted 15 May 2009 Recommended by Christophe D Alessandro The problem of tracking multiple intermittently speaking speakers is difficult as some distinct problems must be addressed. The number of active speakers must be estimated these active speakers must be identified and the locations of all speakers including inactive speakers must be tracked. In this paper we propose a method for tracking intermittently speaking multiple speakers using a particle filter. In the proposed algorithm the number of active speakers is firstly estimated based on the Exponential Fitting Test EFT a source number estimation technique which we have proposed. The locations of the speakers are then tracked using a particle filtering framework within which the decomposed likelihood is used in order to decouple the observed audio signal and associate each element of the decomposed signal with an active speaker. The tracking accuracy is then further improved by the inclusion of a silence region detection step and estimation of the noise-only covariance matrix. The method was evaluated using live recordings of 3 speakers and the results show that the method produces highly accurate tracking results. Copyright 2009 Angela Quinlan 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. 1. Introduction The ability to track the .

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