scholarly journals Efficient database pruning for large-scale cover song recognition

Author(s):  
J. Osmalskyj ◽  
S. Pierard ◽  
M. Van Droogenbroeck ◽  
J.J. Embrechts
Author(s):  
Riyanarto Sarno ◽  
Dedy Rahman Wijaya ◽  
Muhammad Nezar Mahardika

People often have trouble recognizing a song especially, if the song is sung by a not original artist which is called cover song. Hence, an identification system might be used to help recognize a song or to detect copyright violation. In this study, we try to recognize a song and a cover song by using the fingerprint of the song represented by features extracted from MPEG-7. The fingerprint of the song is represented by Audio Signature Type. Moreover, the fingerprint of the cover song is represented by Audio Spectrum Flatness and Audio Spectrum Projection. Furthermore, we propose a sliding algorithm and k-Nearest Neighbor (k-NN) with Bhattacharyya distance for song recognition and cover song recognition. The results of this experiment show that the proposed fingerprint technique has an accuracy of 100% for song recognition and an accuracy of 85.3% for cover song recognition.


2016 ◽  
Vol 6 (1) ◽  
Author(s):  
L. W. Lehnert ◽  
K. Wesche ◽  
K. Trachte ◽  
C. Reudenbach ◽  
J. Bendix

Author(s):  
J. R. A. Giles

AbstractSystematic, large-scale, aerial photography is now available for many areas of the exposed coalfields. In West Yorkshire 1:10000 or 1:10 560 scale cover is generally available, supplemented by 1:5000 and 1:3000 cover in more limited areas. Examination of aerial photographs, in conjunction with detailed geological mapping, has identified characteristic ground patterns associated with the existence of former shallow workings. These patterns are interpreted in terms of changes of style of mining with increasing depth.The presence of shallow mine workings is a major constraint on planning in areas of exposed coalfield. The examination of large scale aerial photographs offers a rapid reconnaissance method of identifying such workings.


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