【摘要】：根據(jù)國際知識產(chǎn)權(quán)聯(lián)盟的統(tǒng)計,每年因數(shù)字音樂的版權(quán)問題帶來的損失已經(jīng)高達(dá)17億美元,給數(shù)字音樂版權(quán)所有人帶來巨大損失,因此很多版權(quán)所有人都不愿輕易公開其所擁有的數(shù)字音樂,這在一定程度上阻礙了數(shù)字音樂自身的發(fā)展和傳播。為了使數(shù)字音樂快速健康的發(fā)展,亟需采取有效的數(shù)字音樂版權(quán)檢測手段對數(shù)字音樂侵權(quán)行為進(jìn)行發(fā)現(xiàn)和檢測,為數(shù)字音樂版權(quán)所有人提供法律維權(quán)依據(jù)來保護(hù)其權(quán)益。 本文提出了一種基于互聯(lián)網(wǎng)的數(shù)字音樂的盜版檢測的解決方案：采用云存儲技術(shù)和數(shù)字音樂特征備案技術(shù)對數(shù)字音樂進(jìn)行基本信息備案、特征備案和授權(quán)備案；采用數(shù)字音樂網(wǎng)絡(luò)爬取技術(shù)對互聯(lián)網(wǎng)上的數(shù)字音樂進(jìn)行爬取并提取和存儲其特征信息；使用特征詞袋模型相似度檢索算法對申請檢測的備案音樂和網(wǎng)絡(luò)爬取的音樂進(jìn)行特征相似度檢索；根據(jù)數(shù)字音樂特征相似度檢索結(jié)果、數(shù)字水印、授權(quán)備案信息生成檢測報告。 本文主要的創(chuàng)新點如下： 一、提出了一個數(shù)字音樂特征詞袋模型相似度檢索算法,該算法通過把音樂特征聚類成音頻詞,形成音頻詞出現(xiàn)次數(shù)的音頻詞直方圖,并通過余弦相似度算法計算數(shù)字音樂的相似度。 二、提出了一個有效的基于互聯(lián)網(wǎng)的數(shù)字音樂盜版檢測方案,該方案實現(xiàn)了數(shù)字音樂的備案、基于互聯(lián)網(wǎng)的數(shù)字音樂抓取、特征提取和特征相似度檢索,最終生成檢測報告為維權(quán)行為提供依據(jù)。 實現(xiàn)結(jié)果表明：本文實現(xiàn)數(shù)字音樂網(wǎng)絡(luò)抓取、特征提取和特征相似度檢索技術(shù)來定位數(shù)字音樂的盜版源,能夠有效地對基于互聯(lián)網(wǎng)的數(shù)字音樂侵權(quán)行為進(jìn)行檢測。
[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.
【學(xué)位授予單位】：北方工業(yè)大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2013
【分類號】：TP391.3

【參考文獻(xiàn)】

相關(guān)期刊論文 前5條

1 韓一;王國胤;楊勇;;基于MFCC的語音情感識別[J];重慶郵電大學(xué)學(xué)報(自然科學(xué)版);2008年05期

2 周軼男;王宇;;Hadoop文件系統(tǒng)性能分析[J];電子技術(shù);2011年05期

3 卓秀然;趙伯聽;郭國洪;林欣;;基于網(wǎng)絡(luò)爬蟲的輿情信息采集系統(tǒng)設(shè)計與實現(xiàn)[J];福建電腦;2012年04期

4 郭興吉;范秉琪;;基于特征的音頻比對技術(shù)[J];河南師范大學(xué)學(xué)報(自然科學(xué)版);2006年02期

5 楊文,丁友東;數(shù)字水印移動代理[J];計算機(jī)應(yīng)用;2001年S1期

相關(guān)碩士學(xué)位論文 前6條

1 李小紅;基于自舉的弱指導(dǎo)中文語義關(guān)系抽取研究[D];蘇州大學(xué);2010年

2 高彥;基于相似度的音頻檢索系統(tǒng)的設(shè)計與實現(xiàn)[D];復(fù)旦大學(xué);2011年

3 謝瑩;論數(shù)字時代音樂版權(quán)的保護(hù)與調(diào)節(jié)[D];武漢大學(xué);2004年

4 張婭;數(shù)字音樂版權(quán)侵權(quán)問題研究[D];華中師范大學(xué);2007年

5 徐昕;現(xiàn)代信息技術(shù)下傳統(tǒng)報業(yè)發(fā)展對策研究[D];哈爾濱工業(yè)大學(xué);2007年

6 夏妍妍;基于RBF神經(jīng)網(wǎng)絡(luò)的語音識別方法的應(yīng)用研究[D];大連海事大學(xué);2008年

，

本文編號：2426103