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研究生: 梁文翰
Wen-han Liang
論文名稱: 以片段抽取和模糊比對為基礎的音樂旋律檢索方法
Music Information Retrieval Based On Pattern Extraction and Fuzzy Matching
指導教授: 林伯慎
Bor-shen Lin
口試委員: 楊傳凱
Chuan-kai Yang
古鴻炎
Hung-yan Gu
學位類別: 碩士
Master
系所名稱: 管理學院 - 資訊管理系
Department of Information Management
論文出版年: 2011
畢業學年度: 100
語文別: 中文
論文頁數: 69
中文關鍵詞: 音樂檢索N-gram前綴樹模糊比對
外文關鍵詞: Music Retrieval, N-gram, Prefix Tree, Fuzzy Match
相關次數: 點閱:191下載:7
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一般內涵式音樂資訊檢索的作法,是先將查詢旋律轉為特徵序列,再與資料庫所有的樂曲做動態比對以找出目標歌曲。但是這種作法會隨著資料庫音樂數量或特徵序列長度的增加導致搜尋時間線性增加,而難以達到即時查詢的目的。本論文抽取出音樂文件集中具有重複性和鑑別力的旋律片段,建立「旋律片語辭典」。如此,便能將文件檢索的方法應用至音樂檢索中。實驗結果顯示,透過「旋律片語辭典」的協助進行音樂檢索,能在短時間之內找到目標樂曲。在不過度犧牲平均排名的情況下,經由篩選片語辭典去除其中較不具鑑別力的旋律片段,可以大幅度降低比對時間。另外,對於哼唱檢索可能出現的錯音問題,我們提出片段擴展的方法,能夠有效提升目標歌曲在哼唱搜索時的平均排名。本論文也提出並比較了兩種查詢旋律和樂曲間的模糊比對公式以計算的相似度。在目標歌曲的檢索上,我們發現非對稱距離比對稱距離效能為佳。在非目標歌曲的檢索上,模糊距離度量比起精確距離度量,所找出的非目標歌曲與目標歌曲間有更高的平均旋律相似度;也就是說,模糊比對有助於找到和目標歌曲旋律近似的非目標歌曲。這樣的特性使音樂檢索系統可應用於探索或分析具有在旋律上具相關性的樂曲。


Conventional content-based music information retrieval (CBMIR) approaches usually convert queries into feature sequences and dynamically compare them with those of the documents in the music database based on dynamic programming so as to find out the target document. However, with the increase of the amount of the collections or the dimension of the feature sequences, the required computation time increases linearly, which makes real-time retrieval for large music database difficult. This paper proposes a retrieval method based on repeated and discriminative melody patterns extracted from music collections, through which the techniques of document retrieval can be applied to CBMIR. Experimental results show that, the search time is relatively short, and can be further reduced by eliminating less discriminative patterns without sacrificing the performance heavily. In addition, two fuzzy measures, denoted as symmetric and asymmetric measures respectively, were proposed in this paper for ranking the retrieved documents. It could be found that the asymmetric one achieves better average ranking for the target document. Additionally, for asymmetric measure, higher average similarity of the non-target documents with the target document can be achieved when compared with symmetric measure and conventional non-fuzzy cosine similarity. The proposed fuzzy matching is helpful for discovering novel and relevant music documents that have patterns similar to the target document, and can potentially be applied to the analysis of music documents with melodic relevance.

第1章 緒論 1 1.1 研究動機 1 1.2 背景簡介 2 1.3 論文目的與成果簡介 4 1.4 論文組織與架構 4 第2章 文獻與背景技術 6 2.1 音樂資訊檢索 6 2.1.1 主旋律抽取 7 2.1.2 主旋律標準化 9 2.1.3 相似度測量 11 2.2 重複片段抽取 14 2.3 前綴樹 17 2.4 動態時間校準 18 2.5 本章摘要 20 第3章 旋律片段抽取 21 3.1 抽取旋律流程 22 3.2 音符編碼 22 3.3 以旋律片段建立前綴樹 23 3.4 旋律片段篩選 26 3.5 旋律片段排序 28 3.6 本章摘要 29 第4章 旋律檢索方法 30 4.1 旋律相似度計算 30 4.2 片段擷取 32 4.3 模糊比對公式 34 4.4 本章摘要 37 第5章 實驗與分析 38 5.1 系統架構 38 5.2 資料前處理 39 5.3 實驗分析 40 5.3.1 音符編碼對查詢效能的影響 41 5.3.2 篩選旋律片段對查詢效能的影響 42 5.3.3 量化等級對查詢效能的影響 44 5.3.4 擷取旋律比例對查詢效能的影響 45 5.3.5 片段擴展對查詢效能的影響 47 5.3.6 哼唱錯誤比例對查詢效能的影響 49 5.3.7 哼唱查詢中篩選旋律片段對查詢效能的影響 50 5.3.8 非目標樂曲旋律相似度比較 51 5.4 本章摘要 52 第6章 結論與未來研究方向 54 6.1 結論 54 6.2 未來研究方向 55 參考文獻 56

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