政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/57079
English  |  正體中文  |  简体中文  |  Post-Print筆數 : 27 |  全文笔数/总笔数 : 109948/140897 (78%)
造访人次 : 46082805      在线人数 : 1141
RC Version 6.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
搜寻范围 查询小技巧:
  • 您可在西文检索词汇前后加上"双引号",以获取较精准的检索结果
  • 若欲以作者姓名搜寻,建议至进阶搜寻限定作者字段,可获得较完整数据
  • 进阶搜寻


    请使用永久网址来引用或连结此文件: https://nccur.lib.nccu.edu.tw/handle/140.119/57079


    题名: 中文流行音樂詞曲情意關聯分析
    Conception association analysis between lyrics and music of Chinese popular music
    作者: 林志傑
    Lin, Chih Chieh
    贡献者: 沈錳坤
    張寶芳

    Shan, Man Kwan
    Chang, Pao Fang

    林志傑
    Lin, Chih Chieh
    关键词: 詞曲情意關聯分析
    音樂情意分析
    歌詞情意分析
    跨模態關聯探勘
    以曲找詞
    音樂資訊擷取
    Conception association analysis between lyrics and music
    Music conception analysis
    Lyrics conception analysis
    Cross modal association mining
    Recommendation lyrics by song
    Music Information Retrieval
    日期: 2012
    上传时间: 2013-03-01 09:27:38 (UTC+8)
    摘要: 本篇論文旨在研究中文流行音樂歌詞與歌曲之間情意的關聯性,並設計一個能推薦出符合歌曲情意的「以曲找詞歌詞推薦系統」。

    流行音樂(Popular Music)在廣義上的定義為透過大眾媒體傳播、以大眾為閱聽對象的歌曲。其大眾化的特徵,使得流行音樂歌詞的主題多與日常生活息息相關且能清楚表達歌曲的情意,並以其所引起的共鳴性決定歌曲是否具出版的商業價值,人們也常常使用流行音樂歌曲來唱出屬於自己的故事、屬於自己的心聲。因此,本篇論文提出自動為流行音樂歌曲推薦符合歌曲情意的歌詞,讓舊有的歌曲搭配上新的歌詞,而當一首歌曲搭配了不同的歌詞就有了不同的故事,也帶給了原曲新的生命,達成一曲多詞的數位加值效果。

    由文獻及專業音樂創作者的論述中,我們可以了解流行音樂詞曲有相關的搭配關係,其中又以詞曲情意的搭配關係最為重要,因此詞曲情意之間的關聯性為本研究問題的核心所在。透過大量分析市面上的流行歌曲,我們便可以從中看出詞曲之間情意搭配的線索。我們利用 LSA(Latent Semantic Analysis)演算法萃取出歌詞的情意特徵值,並比較其與語言學領域中隱喻融合理論的相似性,而在歌曲方面萃取出音高、調性、速度、節奏、和弦及音色等與等能展現歌曲情意的相關特徵值。然後利用了 CFA(Cross-Modal Factor Analysis)演算法來建立詞曲之間情意特徵值的關聯模型,最後我們便可以利用關聯模型來建立推薦系統,如此便完成了詞曲情意關聯為基礎的以曲找詞歌詞推薦系統。

    實驗結果顯示,考慮詞曲情意特徵關聯所訓練出的關聯模型(CFA Feature Model)在以曲找詞推薦符合情意歌詞的前五名準確率平均達 60.1 %,前五十名也有 41.4 % 的準確率,比起僅考慮歌曲情意特徵(Audio Feature Model)以曲找詞推薦符合情意歌詞的前五名準確率 45.1% 及前五十名準確率28.6 % 準確率高,代表本研究所提出的詞曲情意關聯模型確實能有效推薦出符合歌曲情意的歌詞。我們也對本研究提出的詞曲情意關聯模型進行歌詞推薦結果的案例分析,我們輸入幾首學生創作的歌曲觀察詞曲情意關聯模型歌詞推薦結果,我們發現推薦出的流行音樂歌詞與學生創作的原詞在歌詞情意上非常類似,再次顯示本研究所提出的詞曲情意關聯模型確實能有效推薦出符合歌曲情意的歌詞,在詞曲創作上將能為創作者帶來靈感支援,幫助創作者詞曲創作。
    Nowadays lots of people use popular music to sing out their own story, and their own aspirations. In this thesis, we propose an approach to analyze the conception association between lyrics and music of Chinese popular music. And for applications, we design a lyrics recommendation system which can automatically recommend lyrics which is suitable to accompany with query music according to the affection and conception between lyrics and music. So, the old song with new lyrics, just like the song with different stories, brings the original song with new life.

    There are accompany association between lyrics and music, and the affection and conception association is most important among all. Therefore, analyze the conception association between lyrics and music is our goal. To do this, we can find out the association clues between lyrics and music from analyzing lots of popular music. For lyrics, we use LSA (Latent Semantic Analysis) algorithm to extract lyrics conception features. For music, we extracted the pitch, tonality, speed, rhythm, chords features which can show the music’s conception in the music. Then we use the CFA (Cross-Modal Factor Analysis) algorithm to analyze and learn the conception association between lyrics and music and establish the conception association model . Finally, we will be able to take advantage of the conception association model to establish the lyrics recommendation system.

    In the experimental results, when recommend the same conception lyrics to the query music, our proposed approach (CFA Feature Model) reaches accuracy of 60.1% on average in the top 5 recommended lyrics. Compared to control group approach (Audio Feature Model) only reaches accuracy of 45.1% on average in the top 5 recommended lyrics, our approach get better accuracy. We also presented some interesting lyrics recommendation results in case study. We upload some popular music created by students, and we found out that the affection and conception of the recommended lyrics are similar to the original song lyric which is created by the students. The experimental results show that the lyrics and music conception association model we proposed in this study does recommended lyrics suitable to the query music conception.
    參考文獻: [1] K. Bischoff, C. S. Firan, R. Paiu, W. Nejdl, C. Laurier, and M. Sordo, “Music Mood And Theme Classifcation – A Hybrid Approach,” International Society for Music Information Retrieval Conference, 2009.
    [2] M. M. Bradley and P. J. Lang, “Affective Norms for English Words (ANEW),” The NIMH Center for The Study of Emotion and Attention, 1999.
    [3] R. Cai, C. Zhang, L. Zhang, and W. Y. Ma, “MusicSense: Contextual Music Recommendation using Emotional Allocation Modeling,” ACM International Conference on Multimedia, 2007.
    [4] S. Deerwester, S. T. Dumais, G. W. Furnas, T. K. Landauer, and R. Harshman, “Indexing by Latent Semantic Analysis,” Journal of the American Society for Information Science, Vol. 41, No. 6, Pages 391-407, 1990.
    [5] Y. Hu, X. Chen, and D. Yang, “Lyric-based Song Emotion Detection with Affective Lexicon and Fuzzy Clustering Method,” International Society for Music Information Retrieval Conference, 2009.
    [6] X. Hu, J. S. Downie, C. Laurier, M. Bay, and A. F. Ehmann, “The 2007 MIREX Audio Mood Classification Task: Lessons Learned,” International Society for Music Information Retrieval, 2008.
    [7] K. S. Jones, “A Statistical Interpretation of Term Specificity and Its Application in Retrieval,” Journal of Documentation, Vol. 28, Pages 11-24, 1972.
    [8] P. Juslin and P. Luakka, “Expression, Perception, and Induction of Musical Emotions: A Review and Questionnaire Study of Everyday Listening,” Journal of New Music Research, Vol. 33, Issue 3, Pages 217-238, 2004.
    [9] Y. E. Kim, E. M. Schmidt, R. Migneco, B. G. Morton, P. Richardson, J. Scott, J. A. Speck, and D. Turnbull, “Music Emotion Recognition: A State of The Art Review,” International Society for Music Information Retrieval Conference, 2010.
    [10] W. Krzanowski, “Principles of Multivariate Analysis.,” Oxford University Press, 1988.
    [11] D. Li, N. Dimitrova, M. Li, and I. K. Sethi, “Muiltimedia Content Processing through Cross-Modal Association,” ACM International Conference on Multimedia, 2003.
    [12] A. Mehrabian and J. A. Russell, “An Approach to Environmental Psychology, ” MIT Press, 1974.
    [13] O. C. Meyers, “A Mood-Based Music Classification and Exploration System,” Master’s thesis, Massachusetts Institute of Technology, 2007.
    [14] J. A. Russell, “A Circumspect Model of Affect,” Journal of Psychology and Social Psychology, Vol. 39, No. 6, Page 1161, 1980.
    [15] F. Turner, G. Turner, and Mark Turner, “The Way We Think: Conceptual Blending and the Mind’s Hidden Complexities,” New York: Basic Books, 2002.
    [16] L. Zhuang, Z. Ye, J. Wu, F. Zhou, and J. Shao, “Towards a New Reading Experience via Semantic Fusion of Text and Music,” ACM/IEEE Joint Conference on Digital Libraries, 2003.
    [17] 吳媺婉 ,《台灣國語流行歌曲的修辭藝術》,國立台北教育大學語言教育研究所碩士論文,2005。
    [18] 李雙澤,http://zh.wikipedia.org/wiki/%E6%9D%8E%E9%9B%99%E6%BE%A4。
    [19] 周世箴 ,《我們賴以生存的譬喻》,聯經出版公司,2006。
    [20] 林岑陵 ,《中國詩詞空間意境的概念在我音樂創作中的實踐》,國立師範大學音樂研究所博士論文,2010。
    [21] 姚霎珊,〈談談流行歌曲歌時的語言特色〉,《楚雄獅專學報》,1999。
    [22] 柳飛,〈通俗歌曲界定之管見〉,《常州工學院學報》,2006。
    [23] 胡逆天,〈流行歌曲的定義問題〉,《流行詞話》,第三期,2011。
    [24] 馬春樹,〈流行歌詞的比喻特色及其文化透視〉,《廣西大學學報》,2004。
    [25] 張雯禎,《台灣流行歌詞中的隱喻:以愛情為主題(1990-2008)》,國立中正大學語言學研究所碩士論文,2008。
    [26] 陳清橋,《情感的實踐:香港流行歌詞研究》,牛津大學出版社,1997。
    [27] 曾慧佳,《從流行歌曲看台灣社會》,桂冠出版社,1998。
    [28] 華語流行音樂,http://zh.wikipedia.org/wiki/%E8%8F%AF%E8%AA%9E%E6%B5%81%E8%A1%8C%E9%9F%B3%E6%A8%82。
    [29] 費良華,〈流行歌曲歌詞的語法規範問題〉,《白城師範高等專科學校學報》,2002。
    [30] 黃志華,《粵語歌詞》,三聯書店有限公司,2003。
    [31] 劉偉萍,〈通俗歌曲歌詞的修辭藝術〉,《漯河職業技術學院學報》,2003。
    [32] 鄭淑儀,《台灣流行音樂與大眾文化》,輔仁大學大眾傳播所碩士論文,1992。
    [33] 謝峰賜,《簡易詞曲創作入門》,新鳴遠出版有限公司,1993。
    [34] 簡妙如,《流行文化,美學,現代性:以八、九〇年代臺灣流行音樂的歷史重構為例》,國立政治大學新聞研究所博士論文,2002。
    [35] 蘇郁慧,〈青少年流行音樂偏好、態度與音樂環境之相關研究〉,《藝術教育研究》,2005。
    描述: 碩士
    國立政治大學
    數位內容碩士學位學程
    99462010
    101
    資料來源: http://thesis.lib.nccu.edu.tw/record/#G0099462010
    数据类型: thesis
    显示于类别:[數位內容碩士學位學程] 學位論文
    [數位內容與科技學士學位學程] 學位論文

    文件中的档案:

    没有与此文件相关的档案.



    在政大典藏中所有的数据项都受到原著作权保护.


    社群 sharing

    著作權政策宣告 Copyright Announcement
    1.本網站之數位內容為國立政治大學所收錄之機構典藏,無償提供學術研究與公眾教育等公益性使用,惟仍請適度,合理使用本網站之內容,以尊重著作權人之權益。商業上之利用,則請先取得著作權人之授權。
    The digital content of this website is part of National Chengchi University Institutional Repository. It provides free access to academic research and public education for non-commercial use. Please utilize it in a proper and reasonable manner and respect the rights of copyright owners. For commercial use, please obtain authorization from the copyright owner in advance.

    2.本網站之製作,已盡力防止侵害著作權人之權益,如仍發現本網站之數位內容有侵害著作權人權益情事者,請權利人通知本網站維護人員(nccur@nccu.edu.tw),維護人員將立即採取移除該數位著作等補救措施。
    NCCU Institutional Repository is made to protect the interests of copyright owners. If you believe that any material on the website infringes copyright, please contact our staff(nccur@nccu.edu.tw). We will remove the work from the repository and investigate your claim.
    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - 回馈