政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/100461

政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/100461

English | 正體中文 | 简体中文 | Post-Print筆數 : 27 | Items with full text/Total items : 113160/144130 (79%)
Visitors : 50753735 Online Users : 741

RC Version 6.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.

Scope

please add "double quotation mark" for query phrases to get precise results

please goto advance search for comprehansive author search

Adv. Search

Home ‧ Login ‧ Upload ‧ Help ‧ About ‧ Administer

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	Size	Format
601801.pdf	2009Kb	Adobe PDF2	76	View/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