DocumentCode :
595360
Title :
Query by humming via hierarchical filters
Author :
Zhiyuan Guo ; Qiang Wang ; Liang Yin ; Gang Liu ; Jun Guo
Author_Institution :
Pattern Recognition & Intell. Syst. Lab., Beijing Univ. of Posts & Telecommun., Beijing, China
fYear :
2012
fDate :
11-15 Nov. 2012
Firstpage :
3021
Lastpage :
3024
Abstract :
This paper proposes an effective implementation of query by humming (QBH) system via hierarchical filters. Firstly locality sensitive hashing (LSH) is used to screen candidate fragments. Secondly linear scaling (LS) is applied to filter out more false candidates and a new method called linear alignment (LA) is presented to locate accurate boundaries of fragments. Then recursive alignment (RA) is employed for the remaining ones. Finally, scores of scaling factor (SF) is fused with scores of RA to rank the songs. Experiments conducted on a database of 5,000 MIDI files show that the proposed approach achieved the relative improvement of mean reciprocal rank up to 37.3% compared with the state-of-the-art method.
Keywords :
audio databases; content-based retrieval; file organisation; filtering theory; music; MIDI files; QBH system; accurate fragment boundary location; content-based music information retrieval; hierarchical filters; linear alignment; linear scaling; locality sensitive hashing; mean reciprocal rank; query-by-humming system; recursive alignment; scaling factor; screen candidate fragments; Databases; Feature extraction; Filtering algorithms; Matched filters; Maximum likelihood detection; Nonlinear filters; Vectors;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Pattern Recognition (ICPR), 2012 21st International Conference on
Conference_Location :
Tsukuba
ISSN :
1051-4651
Print_ISBN :
978-1-4673-2216-4
Type :
conf
Filename :
6460801
Link To Document :
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