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| Title: | 華語流行音樂之詞式分析與詞曲結構搭配之排比與同步
Lyrics Form Analysis for Chinese Pop Music with Application to Structure Alignment between Lyrics and Melody |
| Authors: | 范斯越
Fan, Sz Yue |
| Contributors: | 沈錳坤
Shan, Man Kwan
范斯越
Fan, Sz Yue |
| Keywords: | 詞式分析
詞曲排比
華語流行音樂
重複樣式探勘
Lyrics Form Analysis
Lyrics Melody Alignment
Chinese Pop Music
Repeating Pattern Mining |
| Date: | 2012 |
| Issue Date: | 2012-11-01 13:58:29 (UTC+8) |
| Abstract: | 目前大部分的聽眾主要是透過歌詞與樂曲的搭配來了解音樂所要表達的內容，因此歌詞創作在目前的音樂工業是很重要的一環。一般流行音樂創作是由作曲人與作詞人共同完成，然而有另一種方式是將既有的詩詞做為歌詞，接著重新譜曲的方式產生新的流行音樂。這種創作方式是讓舊有的詞或曲注入新的生命力，得以流傳到現在。因此本研究希望可以為一首旋律推薦適合配唱的歌詞，以對數位音樂達到舊曲新詞的加值應用。本論文包括兩個部分，分別為：(1)自動分析歌詞的詞式，找出每個段落的位置與其段落的標籤；(2)詞曲結構搭配，找出相符合結構的詞與曲，並且同步每個漢字與音符。
本論文的第一部分為詞式分析，首先將歌詞擷取四個面向的特徵值，分別為(1)句字數結構；(2)拼音結構；(3)詞性；(4)聲調音高。第二步驟，利用這四種特徵值分別建立詞行的自相似度矩陣(Self Similarity Matrix)，並且利用這四個特徵的自相似度矩陣產生一個線性組合自相似度矩陣。第三步驟，建立在自相似度矩陣上我們做段落分群以及家族(Family)組合找出最佳的分段方式，最後將找出的分段方式利用我們整理出來的規則讓電腦自動標記段落標籤。第二部分為詞曲結構搭配，首先我們將主旋律的樂句以及歌詞的詞句做第一層粗略的對應，第二步驟，將對應好的樂句與詞句做第二層漢字與音符細部的對應，最後整合兩層對應的成本當做詞曲搭配的分數。
我們以KKBOX音樂網站當做歌詞來源，並且請專家標記華語流行歌詞資料庫的詞式。實驗顯示詞式分析的Pairwise f-score準確率達到0.83，標籤回復準確率達到0.78。詞曲結構搭配中，查詢的歌曲其原本搭配的歌詞，推薦排名皆為第一名。
Nowadays, lots of pop music audiences understand the content of music via lyrics and melody collocation. In general, a Chinese pop music is produced by composer and lyricist cooperatively. However, another producing manner is composing new melody with ancient poetry. Therefore, we want to recommend present lyrics for a melody and then achieving value-added application for digital music. This thesis includes two subjects. The first subject is lyrics form analysis. This subject is finding the block of verse, chorus, etc., in lyrics. The second subject is structure alignment between lyrics and melody. We utilize the result of lyrics form analysis and then employ a 2-tier alignment to recommend present lyrics which is suitable for singing.
In lyrics form analysis, the first step, we investigate four types of feature from lyrics: (1) Word Count Structure; (2) Pinyin Structure; (3) Part of Speech Structure; (4) Word Tone Pitch. For the second step, we utilize these four types of feature to construct a SSM(Self Similarity Matrix), and blend these four types of SSM to produce a linear combination SSM. The third step is clustering blocks and finding the best Family combination based on SSM. Finally, a rule-based technique is employed to label blocks of lyrics. For the second subject, the first step is aligning music phrases and lyrics sentences roughly. The second step is aligning a word and a note for corresponding phrase and sentence. Finally, we integrated the cost of two-level alignment regarded as the lyrics and melody collocation score.
We collect lyrics from KKBOX, a music web site, and invite experts label ground truth of lyrics form. The experimental result of lyrics form analysis shows that the proposed method achieves the Pairwise f-score of 0.83, and the Label Recovering Ratio of 0.78. The experiment of structure alignment between lyrics and melody shows that the original lyrics of query melodies are ranked number one. |
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| Description: | 碩士
國立政治大學
資訊科學學系
98753009
101 |
| Source URI: | http://thesis.lib.nccu.edu.tw/record/#G0098753009 |
| Data Type: | thesis |
| Appears in Collections: | [資訊科學系] 學位論文
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