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研究生:傅韶宇
研究生(外文):Shao-YuFu
論文名稱:基底於叢集方法之相同或相似特性音樂搜尋
論文名稱(外文):Music Retrieval with Identical or Relevant Properties Using Clustering Techniques
指導教授:曾新穆曾新穆引用關係
指導教授(外文):Vincent S. Tseng
學位類別:碩士
校院名稱:國立成功大學
系所名稱:資訊工程學系碩博士班
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2012
畢業學年度:100
語文別:英文
論文頁數:59
中文關鍵詞:內涵式音樂檢索音樂辨識相似音樂搜尋二階段叢集法多媒體探勘
外文關鍵詞:Content-based music retrievalMusic identificationRelevant music searchTwo-stage clusteringmultimedia mining
相關次數:
  • 被引用被引用:0
  • 點閱點閱:102
  • 評分評分:
  • 下載下載:6
  • 收藏至我的研究室書目清單書目收藏:0
由於網路和資訊科技的發達,越來越多的影音資料被真實地記錄著。為了要擷取這些珍貴的影音資料,處理多媒體的問題也隨之產生,其中音樂資料之搜尋為最熱門議題之一。然而,由於多媒體資料的多樣性與大量性,再再突顯本研究的挑戰性,當中又以內涵為基礎的音樂搜尋系統(Content-Base Music Retrieval,簡稱CBMR)為近年來研究發展的重點。本研究之目的在於發展一套音樂搜尋系統,能夠有效率地搜尋出相同及相似的音樂,尤其是針對相似的音樂,為了要能同時考慮聽覺與時間的特性,我們利用了二階段叢集法(two-stage clustering),將原始複雜的音樂內涵轉換成知覺樣式;而尋找相同歌曲的部分,則是透過階層式叢集法,將音樂的每個框架進行分群,最後藉由所建構好的索引去進行搜尋且利用平行處理來使搜尋時間縮短。實驗結果顯示出我們的方法在搜尋相同及相似歌曲上於準確率及效率均有優異之表現。
With the advance of network and information technologies, more and more audio and video data have been truly recorded. Therefore, in recent years, how to retrieve the interested music from a huge amount of multimedia data is has been a challenging issue, especially for music. In the field of music retrieval, it can generally be divided into two types: identical and relevant music retrieval. Basically, a successful identical music retrieval indicates that the retrieved result is the same as the query, while a successful relevant music retrieval indicates that the retrieved results are just similar to the query. Accordingly, the purpose of our research is to develop a music retrieval system that can retrieve the identical and relevant music effectively and efficiently. For relevant music retrieval, in order to consider acoustical and temporal features simultaneously, we propose a two-stage clustering method to convert musical contents into perceptual patterns. As for the part of identical music retrieval, time cost is reduced significantly by hierarchical clustering and parallel computation. The experimental results reveal that our proposed music retrieval approaches are very effective and efficient in both of identical and relevant music retrieval.
ABSTRACT I
摘要 III
誌謝 IV
CONTENTS V
List of Tables VII
List of Figures VIII
Chapter 1 Introduction 1
1.1 Background 1
1.2 Motivation 3
1.3 Overview of Proposed Method 4
1.4 Contributions 5
1.5 Thesis Organization 6
Chapter 2 Related Work 7
2.1 The Low Level Features of Music 7
2.2 Similarity of Sequence Comparison 8
2.3 Music Information Retrieval System 10
2.3.1 Identical Music Retrieval 11
2.3.2 Relevant Music Retrieval 12
Chapter 3 Proposed Approach 13
3.1 The Framework of Music Retrieval System 14
3.2 Offline Stage 15
3.2.1 MFCC Features Extraction 16
3.2.2 Feature Symbolization 17
3.3 Online Stage 26
3.3.1 Identical Music Retrieval in Online Stage 26
3.3.2 Relevant Music Retrieval in Online Stage 29
Chapter 4 Experimental Evaluation 32
4.1 Experimental Setting 32
4.1.1 Experimental Data 32
4.1.2 Experimental Design 34
4.1.3 Experimental Measurement 36
4.2 Experimental Results 37
4.2.1 Identical Music Retrieval 37
4.2.2 Relevant Music Retrieval 43
4.3 Discussions on Experimental Results 50
Chapter 5 Conclusions and Future Work 51
5.1 Conclusions 51
5.2 Future Work 52
References 53
VITA 59
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