基于互联网的数字音乐盗版检测技术应用研究
发布时间：2019-02-18 18:56
【摘要】：根据国际知识产权联盟的统计,每年因数字音乐的版权问题带来的损失已经高达17亿美元,给数字音乐版权所有人带来巨大损失,因此很多版权所有人都不愿轻易公开其所拥有的数字音乐,这在一定程度上阻碍了数字音乐自身的发展和传播。为了使数字音乐快速健康的发展,亟需采取有效的数字音乐版权检测手段对数字音乐侵权行为进行发现和检测,为数字音乐版权所有人提供法律维权依据来保护其权益。 本文提出了一种基于互联网的数字音乐的盗版检测的解决方案：采用云存储技术和数字音乐特征备案技术对数字音乐进行基本信息备案、特征备案和授权备案；采用数字音乐网络爬取技术对互联网上的数字音乐进行爬取并提取和存储其特征信息；使用特征词袋模型相似度检索算法对申请检测的备案音乐和网络爬取的音乐进行特征相似度检索；根据数字音乐特征相似度检索结果、数字水印、授权备案信息生成检测报告。 本文主要的创新点如下： 一、提出了一个数字音乐特征词袋模型相似度检索算法,该算法通过把音乐特征聚类成音频词,形成音频词出现次数的音频词直方图,并通过余弦相似度算法计算数字音乐的相似度。 二、提出了一个有效的基于互联网的数字音乐盗版检测方案,该方案实现了数字音乐的备案、基于互联网的数字音乐抓取、特征提取和特征相似度检索,最终生成检测报告为维权行为提供依据。 实现结果表明：本文实现数字音乐网络抓取、特征提取和特征相似度检索技术来定位数字音乐的盗版源,能够有效地对基于互联网的数字音乐侵权行为进行检测。
[Abstract]:According to the statistics of the International intellectual property Alliance, the annual loss caused by the copyright problem of digital music has reached 1.7 billion US dollars, which has brought huge losses to the copyright holders of digital music. Therefore, many copyright owners are reluctant to easily disclose their own digital music, which to some extent hinders the development and dissemination of digital music itself. In order to make digital music develop rapidly and healthily, it is urgent to adopt effective digital music copyright detection method to detect and detect digital music infringement, and to provide legal basis for digital music copyright owners to protect their rights and interests. In this paper, a solution of digital music piracy detection based on Internet is put forward: cloud storage technology and digital music feature record technology are used to record basic information, feature record and authorized record of digital music; The digital music crawling technology is used to crawl the digital music on the Internet and extract and store its characteristic information. The feature similarity retrieval algorithm is used to retrieve the feature similarity between the recorded music applied for detection and the music crawled on the network. According to the result of digital music feature similarity retrieval, digital watermark and authorization record information are used to generate the detection report. The main innovations of this paper are as follows: first, a similarity retrieval algorithm of digital music feature word bag model is proposed. By clustering the music features into audio words, the audio word histogram is formed. The similarity of digital music is calculated by cosine similarity algorithm. Secondly, an effective digital music piracy detection scheme based on the Internet is proposed, which realizes the recording of digital music, the capture of digital music based on the Internet, feature extraction and feature similarity retrieval. Finally, the test report is generated to provide the basis for the action of safeguarding rights. The results show that: this paper implements digital music network capture, feature extraction and feature similarity retrieval technology to locate the source of digital music piracy, can effectively detect digital music infringement based on the Internet.
【学位授予单位】：北方工业大学
【学位级别】：硕士
【学位授予年份】：2013
【分类号】：TP391.3
本文编号：2426103
[Abstract]:According to the statistics of the International intellectual property Alliance, the annual loss caused by the copyright problem of digital music has reached 1.7 billion US dollars, which has brought huge losses to the copyright holders of digital music. Therefore, many copyright owners are reluctant to easily disclose their own digital music, which to some extent hinders the development and dissemination of digital music itself. In order to make digital music develop rapidly and healthily, it is urgent to adopt effective digital music copyright detection method to detect and detect digital music infringement, and to provide legal basis for digital music copyright owners to protect their rights and interests. In this paper, a solution of digital music piracy detection based on Internet is put forward: cloud storage technology and digital music feature record technology are used to record basic information, feature record and authorized record of digital music; The digital music crawling technology is used to crawl the digital music on the Internet and extract and store its characteristic information. The feature similarity retrieval algorithm is used to retrieve the feature similarity between the recorded music applied for detection and the music crawled on the network. According to the result of digital music feature similarity retrieval, digital watermark and authorization record information are used to generate the detection report. The main innovations of this paper are as follows: first, a similarity retrieval algorithm of digital music feature word bag model is proposed. By clustering the music features into audio words, the audio word histogram is formed. The similarity of digital music is calculated by cosine similarity algorithm. Secondly, an effective digital music piracy detection scheme based on the Internet is proposed, which realizes the recording of digital music, the capture of digital music based on the Internet, feature extraction and feature similarity retrieval. Finally, the test report is generated to provide the basis for the action of safeguarding rights. The results show that: this paper implements digital music network capture, feature extraction and feature similarity retrieval technology to locate the source of digital music piracy, can effectively detect digital music infringement based on the Internet.
【学位授予单位】：北方工业大学
【学位级别】：硕士
【学位授予年份】：2013
【分类号】：TP391.3
【参考文献】
相关期刊论文 前5条
1 韩一;王国胤;杨勇;;基于MFCC的语音情感识别[J];重庆邮电大学学报(自然科学版);2008年05期
2 周轶男;王宇;;Hadoop文件系统性能分析[J];电子技术;2011年05期
3 卓秀然;赵伯听;郭国洪;林欣;;基于网络爬虫的舆情信息采集系统设计与实现[J];福建电脑;2012年04期
4 郭兴吉;范秉琪;;基于特征的音频比对技术[J];河南师范大学学报(自然科学版);2006年02期
5 杨文,丁友东;数字水印移动代理[J];计算机应用;2001年S1期
相关硕士学位论文 前6条
1 李小红;基于自举的弱指导中文语义关系抽取研究[D];苏州大学;2010年
2 高彦;基于相似度的音频检索系统的设计与实现[D];复旦大学;2011年
3 谢莹;论数字时代音乐版权的保护与调节[D];武汉大学;2004年
4 张娅;数字音乐版权侵权问题研究[D];华中师范大学;2007年
5 徐昕;现代信息技术下传统报业发展对策研究[D];哈尔滨工业大学;2007年
6 夏妍妍;基于RBF神经网络的语音识别方法的应用研究[D];大连海事大学;2008年
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