tailieunhanh - Báo cáo hóa học: " Research Article Bird Species Recognition Using Support Vector Machines"

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 Bird Species Recognition Using Support Vector Machines | Hindawi Publishing Corporation EURASIP Journal on Advances in Signal Processing Volume 2007 Article ID 38637 8 pages doi 2007 38637 Research Article Bird Species Recognition Using Support Vector Machines Seppo Fagerlund Laboratory of Acoustics and Audio Signal Processing Helsinki University of Technology . Box3000 02015 TKK Finland Received 13 November 2006 Revised 20 February 2007 Accepted 31 March 2007 Recommended by Satya Dharanipragada Automatic identification of bird species by their vocalization is studied in this paper. Bird sounds are represented with two different parametric representations i the mel-cepstrum parameters and ii a set of low-level signal parameters both of which have been found useful for bird species recognition. Recognition is performed in a decision tree with support vector machine SVM classifiers at each node that perform classification between two species. Recognition is tested with two sets of bird species whose recognition has been previously tested with alternative methods. Recognition results with the proposed method suggest better or equal performance when compared to existing reference methods. Copyright 2007 Seppo Fagerlund. 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 Interest towards automatic recognition of bird species based on their vocalization has increased and many recent studies have been published 1-5 . Bird species identification is a typical pattern recognition problem and most studies include signal preprocessing feature extraction and classification sections. Bird vocalization segmentation into smaller recognition units is performed by hand or automatically. The number of species has ranged between 2 and 16 in previous studies. The works of Anderson et al. 6 and Kogan and Mar-goliash 7 were among the first attempts to .