FINGERPRINT INFORMATION MAXIMIZATION FOR CONTENT IDENTIFICATION

被引：0
|
作者：
Naini, Rohit [1 ]
Moulin, Pierre [1 ]
机构：
[1] Univ Illinois, Beckman Inst, Coord Sci Lab, 405 N Mathews Ave, Urbana, IL 61801 USA
来源：
2014 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP) | 2014年
关键词：
Audio fingerprinting; Information bottleneck; Information maximization; Content Identification;
D O I：
暂无
中图分类号：
O42 [声学];
学科分类号：
070206 ; 082403 ;
摘要：
This paper presents a novel design of content fingerprints based on maximization of the mutual information across the distortion channel. We use the information bottleneck method to optimize the filters and quantizers that generate these fingerprints. A greedy optimization scheme is used to select filters from a dictionary and allocate fingerprint bits. We test the performance of this method for audio fingerprinting and show substantial improvements over existing learning based fingerprints.
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页数：5
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