基于声学指纹的海量MP3文件近似去重方法  

Near De-duplication Method of Massive MP3 Files Based on Acoustic Fingerprint

作　　者：赵晓永[1] 杨扬[1] 王宁[1] 

机构地区：[1]北京科技大学计算机与通信工程学院,北京100083

出　　处：《计算机工程》2013年第7期73-75,82,共4页Computer Engineering

基　　金：国家自然科学基金资助项目(61070182;61170209)

摘　　要：在互联网中重复上传他人已经分享的歌曲会消耗网络带宽,浪费存储空间,但目前的重复数据删除方法主要基于文件的二进制特征,无法识别经过信号处理或压缩后的歌曲。针对该问题,提出一种基于声学指纹的海量MP3文件近似去重方法。结合文件消息摘要的确定性与声学指纹的鲁棒性,在采用布隆过滤器对文件消息摘要一次去重的基础上,根据降维后的声学指纹值进行二次近似去重,保证高效的同时提高去重率。实验结果表明,与可变分块检测方法相比,该方法的去重率可提高1倍以上,扩展性较好。Song re-uploading bad been shared wastes network bandwidth and storage, which needs to use data de-duplication technology. However, the current approach to de-duplication based file bit-feature does not recognize the same song after signal processing or compression. Aiming at this problem, this paper proposes a near de-duplication method of massive MP3 files based on acoustic fingerprint. It combines the certainty of message digest with the robustness of the acoustic fingerprint, after Bloom Filter（BF） de-duplicate data based on the message digest, then reduces acoustic fingerprint for the secondary near de-duplication based on the dimensionality. It ensures efficient at the same time, greatly improves the de-duplication ratio. Experimental results show that this method can improve the de-duplication rate by one time than Content-defined Chunking（CDC） method, and has good extensibility.

关 键 词：声学指纹 重复数据删除 近似去重 布隆过滤器 海量数据 

分 类 号：TP311[自动化与计算机技术—计算机软件与理论]