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姓名 劉全勇(Chuang-Yeong Lau) 查詢紙本館藏 畢業系所 通訊工程學系 論文名稱 應用模糊類神經網路自動產生音樂旋律之研究
(An Automatic Melody Generation Using Fuzzy Neural Networks)相關論文 檔案 [Endnote RIS 格式]
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至系統瀏覽論文 ( 永不開放)
摘要(中) 過去自動作曲的研究，演算法產生出來的音樂作品並不完全符合音樂理論規則。本篇論文提出的方法為，以流行歌曲中重複率高的副歌旋律作為訓練對象，利用模糊類神經網路(fuzzy neural network, FNN)來產生新的音樂旋律。FNN是使用模糊倒傳遞演算法(fuzzy back-propagation algorithm)，模糊推論可模擬作曲家在創作過程中做決策的概念。產生出來的音樂旋律再以檢查調號(key signature)及協合音程(consonance interval)的方式來調整音符，以致其符合音樂理論。最後模擬的結果顯示，本論文提出的學習演算法擁有良好的學習能力及不錯的表現。
摘要(英) The generated music from automatic music composition is not completely match the rule of music theory in the past research. This thesis proposed using fuzzy neural network (FNN) to training a repeating pattern melody which called refrain in pop music. A refrain usually repeats many times in the music objects. The proposed learning algorithm is based on fuzzy back propagation algorithm (FBP). The main goal of a fuzzy inference system is to model composer decision making within conceptual as the process of composing music. The music theory knowledge of consonance intervals and key signature were adopted to check and adjust the output melody to prevent incorrectly. The simulation results show that the proposed learning algorithm have a good learning ability and well performance.
關鍵字(中) ★ 模糊類神經
★ 樂理
★ 自動作曲關鍵字(英) ★ automatic music composing
★ fuzzy neural network
★ music theory論文目次 目錄
摘 要 i
Abstract ii
誌 謝 iii
圖 目 錄 v
表 目 錄 vi
第一章 緒論 (Introduction) 1
1-1 前言 1
1-2 背景介紹 3
1-3 基礎樂理介紹 6
1-4 本篇論文組織 13
第二章 模糊類神經網路 (Fuzzy neural network) 14
2-1 類神經網路 14
2-2 模糊系統 16
2-3 模糊類神經網路 19
第三章 學習演算法 (Learning algorithm) 22
3-1 倒傳遞演算法 22
3-2 倒傳遞模糊系統 24
3-2-1 權重值wj的倒傳遞修正 24
3-2-2 平均值mj的倒傳遞修正 25
3-2-3 變異數σj的倒傳遞修正 27
第四章 模擬結果 (Simulation results) 28
4-1 系統模擬架構 28
4-2 訓練資料 30
4-3 模擬結果 35
結論 (Conclusion) 41
參考文獻 (References) 42
參考文獻 [1]Mozer MC. "Neural network composition by prediction: Exploring the benefits of psychophysical constraints and multi-scale processing," Connection Science, vol.6, 1994, pp.247-280
[2]Tomasz Oliwa and Markus Wagner, "Composing Music with Neural Networks and Probabilistic Finite-State Machines," Proceedings of the Sixth European Workshop on Evolutionary and Biologically Inspired Music, Sound, Art and Design, Springer Berlin, Springer, pp.503-508
[3]J.L. Hsu, C.C. Liu, and A.L.P. Chen. "Discovering Non-trivial Repeating Patterns in Music Data," IEEE Transactions on Multimedia, vol.3, no.3, Sep. 2001
[4]Ames C, Domino M. "Cybernetic composer: an overview," In Understanding Music with AI, AAAI Press,1992, pp.186-205
[5]B. L. Jacob. "Composing with Genetic Algorithms," In proceedings of the International Computer Music Conference, 1995.
[6]K. Ebcioglu. "An Expert System for Harmonizing Four-part Chorales," Computer Music Journal, 1988, pp.43-51
[7]David. Cope. "Computer Modeling of Musical Intelligence in Experiments in Musical Intelligence," Computer Music Journal, vol.16, no.2, Summer, 1992, pp.69-83
[8]Eerola, T. & Toiviainen, P., MIDI Toolbox: MATLAB Tools for Music Research, University of Jyvaskyla: Kopijyva, Jyvaskyla, Finland, 2004
[9]Krumhansl, C. L. Cognitive Foundations of Musical Pitch, New York: Oxford University Press, 1990
[10]C.T. Chao and C.C.Teng, “Implementation of a fuzzy inference system using a normalized fuzzy neural network,” Fuzzy Sets and Systems, vol.75, no.1, pp.17-31, October 1995. (SCI)
[11]張孝德, 蘇木春, 機器學習:類神經網路、模糊系統以及基因演算法則, 台北：全華科技圖書有限公司, 2004
[12]陳若涵, 許肇凌, 張智星, 羅鳳珠, "以音樂內容為基礎的情緒分析與辨識", 第二屆電腦音樂與音訊技術研討會, Taipei, Taiwan, March 2006.
[13]亞聖, 「音樂旋律自動產生演算法之研究」，碩士論文，國立臺灣大學電機資訊學學院資訊網路與多媒體研究所，台北，2009，取自「台灣大學機構典藏」: http://ntur.lib.ntu.edu.tw/handle/246246/180688
指導教授 賀嘉律(Chia-Lu Ho) 審核日期 2012-8-27 推文 plurk
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