English  |  正體中文  |  简体中文  |  Post-Print筆數 : 27 |  Items with full text/Total items : 113648/144635 (79%)
Visitors : 51688222      Online Users : 550
RC Version 6.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
  • Adv. Search
    HomeLoginUploadHelpAboutAdminister Goto mobile version
    政大典藏 > College of Commerce > Department of MIS > Theses >  Item 140.119/100461
    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/100461


    Title: 吉他和弦把位音訊特徵萃取與辨識系統研究
    Guitar Chord Fret Position Audio Feature Extraction and Recognition System
    Authors: 莊淳中
    Chuang, Chun Chung
    Contributors: 蔡瑞煌
    Tsaih, Rua Huan
    莊淳中
    Chuang, Chun Chung
    Keywords: 音樂資訊檢索
    和弦辨識
    音級輪廓
    梅爾倒頻譜係數
    支撐向量機
    吉他
    Date: 2016
    Issue Date: 2016-08-22 10:45:00 (UTC+8)
    Abstract: 和弦在現代音樂當中扮演重要的角色,它能構成音樂的基礎並能表現多種變化性的聽覺感受。而吉他是一種適合作為演奏和弦的樂器,透過手指選擇在吉他指板上的音符並按壓琴弦,再配合撥弦或刷扣彈奏可以變化出許多不同的和弦。和弦辨識系統是結合音樂理論與電腦運算能力,將聲音訊號當中出現的和弦辨識出來,其已經在音樂資訊檢索領域有許多研究,也開發出許多的應用系統,以往的系統通常只辨識出和弦的名稱,但對於吉他演奏者來說,在吉他上面按壓和弦的把位,會造成音色與和聲的不同,因此本研究透過相關文獻整理,實作一個系統,觀察到音級輪廓與梅爾倒頻譜係數兩種音訊特徵,與支撐向量機監督式機器學習,能達到辨識吉他和弦把位,進而希望得到吉他音樂背後音色與和聲的高階音樂意涵。
    Reference: [1] Baniya, B. K., Ghimire, D. and Lee, J., "Automatic Music Genre Classification Using Timbral Texture and Rhythmic Content Features," ICACT TACT, (3:3), 2014
    [2] Bharucha, J., Krumhansl, C. L., "The representation of harmonic structure in music: Hierarchies of stability as a function of context", Cognition 13, pp. 63-102, 1983
    [3] Corrigall, K. A., and Schellenber., E. G., Handbook of psychology of emotions: Recent theoretical perspectives and novel empirical findings, Nova, Canada, pp. 299-326
    [4] Chien, H. C., Essentials of Guitar (4th ed.), OverTop Music, Taiwan, 2004 (Chinese version)
    [5] Casey, M. A., Veltkamp, R., Goto, M., Leman, M., Rhodes, C. and Slaney, M., "Content-Based Music Information Retrieval: Current Directions and Future Challenges,", Proc. of the IEEE (96:4), April 2008
    [6] Chuan, C. H., and Chew, E., "Audio onset detection using machine learning techniques: the effect and applicability of key and tempo information," Computer Science Department Technical Report, University of Southern California, 2008
    [7] Davis, S. B. and Mermelstein, P., "Comparison of parametric representations for monosyllabic word recognition in continuously spoken sentences," IEEE Transactions on ASSP, (28:4), pp. 357-366, 1980
    [8] Dosenbach, K., Fohl, W. and Meisel, A., "Identification of individual guitar sound by support vector machines," Proc. of the 11th Int. Conference on Digital Audio Effects, 2008
    [9] Dixon, S., "Onset Detection Revisited," Proc. of the 9th International Conference on Digital Audio Effects, 2006
    [10] Fujishima, T., "Real time chord recognition of musical sound: A system using common lisp music," ICMC, pp. 464-467, 1999.
    [11] Fohl, W., Turkalj, I., and Meisel A., "A Feature Relevance Study for Guitar Tone Classification," Proc. of the 13th ISMIR, 2013.
    [12] Gomez, E., Tonal description of music audio signals, Ph.D. thesis, UPF Barcelona, 2006.
    [13] Hrybyk, A. and Kim, Y. E. "Combined audio and video analysis for guitar chord identification," Proc. of the 11th ISMIR, pp.159-164, 2010.
    [14] Lee, J. H., "Supervised Learning for Guitar Chord Voicing Identification Aided by the Use of MIDI Pickups", 2013.
    [15] Lee, K., and Slaney, M., "Automatic Chord Recognition from Audio Using an HMM with Supervised Learning," Proc. of the 7th ISMIR, 2006.
    [16] Liu, J. and Xie, L., "SVM-Based Automatic Classification of Musical Instruments," International Conference on Intelligent Computation Technology and Automation, 2010.
    [17] McFadden, A., "Why 44.1 kHz? Why not 48 kHz?, CD-Recordable FAQ,", March 2016 (available online at http://stason.org/TULARC/pc/cd-recordable/2-35-Why-44-1KHz-Why-not-48KHz.html)
    [18] Mitra, S. L, Digital Signal Processing: A Computer-Based Approach (3rd ed.), 2006.
    [19] Oudre, L., Grenier, Y., and Févotte, C., "Chord Recognition by Fitting Rescaled Chroma Vectors to Chord Templates," IEEE Transactions on Audio, Speech and Language Processing, (19:7), pp.2222-2233, 2011
    [20] Pan, S.W., Guitar Chord Encyclopedia (8th ed.), Vision Quest, Taiwan, 2013 (Chinese version)
    [21] PyMIR, https://github.com/jsawruk/pymir
    [22] Stark, A. M., and Plumbley, M. D., "Real-time Chord Recognition for Live Performance," ICMC, 2009.
    [23] Sheh, A. and Ellis, D. P., "Chord segmentation and recognition using EM-trained hidden Markov models," ISMIR, 2003.
    [24] Shepard, R. N., The Psychology of Music: Structural representations of musical pitch (1st ed.), Swets & Zeitlinger, Deutsch, 1982.
    [25] scikit-learn, http://scikit-learn.org/
    [26] Spark 1.6.1 Mllib Logistic regression, http://spark.apache.org/docs/latest/ml-classification-regression.html#logistic-regression
    [27] Tzanetakis, G., Music Data Mining: An Introduction, pp. 44-46 pp.52.
    [28] Zhang, X., and Ras, Z., "Discriminant feature analysis for music timbre recognition," ECML/PKDD Third International Workshop on Mining Complex Data (MCD 2007), pp. 59-70
    Description: 碩士
    國立政治大學
    資訊管理學系
    103356018
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0103356018
    Data Type: thesis
    Appears in Collections:[Department of MIS] Theses

    Files in This Item:

    File SizeFormat
    601801.pdf2009KbAdobe PDF276View/Open


    All items in 政大典藏 are protected by copyright, with all rights reserved.


    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 ©   - Feedback