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由華語流行歌詞探勘歌詞的特徵樣式 / Mining Patterns from Lyrics of Chinese Popular Music

華語流行歌詞一直是語言、文學、音樂或是文化研究等相關科系赤手可熱的研究題目,內容包含作詞者、修辭分析、風格、用韻及語言表達等,然由於歌詞數量龐大,難以全部以人工分析。
近年來,資訊科技日新月異不斷地進步,隨著Big Data議題受到注目,Data Mining在近年來相當熱門,然而針對華語流行歌詞的巨量資料探勘與分析研究並不多。因此,本論文研究以程式來自動化分析歌詞的樣式與特性,包括詞彙頻率、詞彙相鄰關係分析、歌名分析、使用語系分析、舊曲新唱、歌詞風格自動分類、用韻及修辭等,而研究資料係透過網路擷取知名網站內容,包含魔鏡歌詞網 (Mojim.com)、臺北之音HitFM聯播網 (www.hitoradio.com) 及教育部重編國語辭典,透過分析規則及以Non-Trivial Repeating Pattern等方法,來完成分析及系統實作。
透過華語流行歌詞的大量分析,探勘及了解各種歌詞的風格與特性,將可了解各種歌詞、作詞者的風格與特色,進而應用在歌詞資料的管理與查詢。
此外,本研究將八萬多首歌詞的各種分析資料設置成網站,提供予學術研究使用,希冀此研究資料能使華語流行歌詞相關研究研究,進行更深入地探討。 / Chinese popular music lyrics has been a popular topic for researchers who major in languages and literature, music or culture. Related studies include of lyricists, rhetoric methods, styles, rhyme and language expression. However, all these studies were performed by manual analysis. It is difficult to analyze large amount of lyrics manually.
With advances in computer technology, big data and data mining techniques have been widely used in different kinds of data. However, to the best of our knowledge, none have been done on pattern mining from big data of lyrics of Chinese popular music. Therefore, the objective of this thesis is to discover patterns from tremendous lyrics data based on data mining techniques. We use data downloaded from www.mojim.com, http://dict.revised.moe.edu.tw/cbdic/ and http://www.hitoradio.com (Hit FM). Data mining methods are employed to find lyrics’ patterns and features, including frequent words, word adjacency, analysis of hit songs' names, lyrics’ language studies, cover song research, automatic style prediction, rhyme and rhetoric patterns.
With the analysis of tremendous lyrics and data, the developed approaches of this thesis will be helpful for discovering distinguishing styles of lyrics and lyricists.

Identiferoai:union.ndltd.org:CHENGCHI/G0101971001
Creators周晏如, Chou, Yen Ju
Publisher國立政治大學
Source SetsNational Chengchi University Libraries
Language中文
Detected LanguageEnglish
Typetext
RightsCopyright © nccu library on behalf of the copyright holders

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