Responsive image
博碩士論文 etd-0828107-081254 詳細資訊
Title page for etd-0828107-081254
論文名稱
Title
以音樂分類偵測音樂節奏之方法
Tempo and Beat Tracking for Audio Signals with Music Genre Classification
系所名稱
Department
畢業學年期
Year, semester
語文別
Language
學位類別
Degree
頁數
Number of pages
65
研究生
Author
指導教授
Advisor
召集委員
Convenor
口試委員
Advisory Committee
口試日期
Date of Exam
2007-07-05
繳交日期
Date of Submission
2007-08-28
關鍵字
Keywords
拍子、自動化音樂訊號處理、類神經網路、演奏速度、分類
neural network, tempo, automatic audio processing, classify, beat
統計
Statistics
本論文已被瀏覽 5750 次,被下載 1751
The thesis/dissertation has been browsed 5750 times, has been downloaded 1751 times.
中文摘要
由於(1)MP3壓縮技術的發達,(2)公開平台的進步,(3)MP3隨身碟的發展,科技的日新月異使得現今音樂越來越普遍化。大部分的人幾乎每天都有聽音樂的習慣,在聽音樂的同時,人們有時會跟著音樂哼唱,有時會跟著音樂節奏敲打著。這些情況也隨著每個人的感受而有所不同,因此若我們沒有此音樂的樂譜,我們無法得到很明確的音樂資訊(演奏速度,拍子,旋律…等)。樂譜標示的tempo跟我們直接聽音樂來感受它的tempo有所不同,所以我們會需要一些技巧或方法來分析我們所聽的音樂,並得知我們想要的一些資訊。演奏速度(tempo)和拍子(beat)在感知音樂上是很重要的元素,它們帶有重要的資訊,所以演奏速度評估和拍子追蹤在自動化音樂訊號處理(automatic audio processing)是很重要的技術且對於多媒體的應用亦是一個必要的工作。我們首先使用類神經網路來對音樂分類,然後根據其分類結果使用 Ellis's 或 Dixon's 方法來獲得正確的評tempo和beat。我們使用包含十類音樂類型的混合資料集來測試我們的方法。最後實驗結果也證實我們的方法比單獨使用 Ellis's 或 Dixon's 方法來得準確。
Abstract
In the present day, the music becomes more popular due to the following three reasons: (1) the evolution of the MP3 compression technology, (2) the growth of the public platform, and (3) the development of the MP3 portable discs. Most people follow the music to hum or follow the rhythm to tap sometimes. The meanings of a music style may be various if it is explained or felt by different people. Therefore we cannot obtain a very explicit answer if the notation of the music cannot be exactly made. We need some techniques and methods to analyze the music, and obtain some of its embedded information. Tempo and beats are very important elements in the perceptual music. Therefore, tempo estimation and beat tracking are fundamental techniques in automatic audio processing, which are crucial to multimedia applications. In this thesis, we first develop an artificial neural network to classify the music excerpts into the evaluation preference. And then, with the preference classification, we can obtain accurate estimation for tempo and beats, by either Ellis's method or Dixon's method. We test our method with a mixed data set which contains ten music genres extracted from the "ballroom dancer" database. Our experimental results show that the accuracy of our method is higher than that of only one individual Ellis's method or Dixon's method.
目次 Table of Contents
LIST OF FIGURES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
LIST OF TABLES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .5
ABSTRACT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .0
Chapter 1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . .1
Chapter 2. Preliminaries . . . . . . . . . . . . . . . . . . . . . . . . . . 5
2.1 Onset Detection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .6
2.2 Construction of Automatic Audio Processing . . . . . . .8
2.3 Artificial Neural Networks . . . . . . . . . . . . . . . . . . . . 10
Chapter 3. Related Algorithms . . . . . . . . . . . . . . . . . . . . 15
3.1 Ellis's Method for Beat Tracking . . . . . . . . . . . . . . . .15
3.2 Dixon's Method: Beatroot . . . . . . . . . . . . . . . . . . . . . 16
Chapter 4. Our Method . . . . . . . . . . . . . . . . . . . . . . . . . . .20
4.1 Feature Extraction . . . . . . . . . . . . . . . . . . . . . . . . . . . .22
4.2 Framework of Our Method . . . . . . . . . . . . . . . . . . . . .26
Chapter 5. Experimental Results . . . . . . . . . . . . . . . . . . . .35
Chapter 6. Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . .50
BIBLIOGRAPHY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52
參考文獻 References
[1] Ismir 2007 Homepage." http://ismir2007.ismir.net/.
[2] Ismir Homepage." http://www.ismir.net/.
[3] Mirex 2007 Homepage." http://www.music-ir.org/mirexwiki/index.php.
[4] H. Abdi, "A neural network primer," Journal of Biological Systems, Vol. 2, No. 3, pp. 247{283, 1994.
[5] M. A. Alonso, B. David, and G. Richard, "A study of tempo tracking algorithms from polyphonic music signals," Proceedings of the 4th COST 276 Workshop, Bordeaux, France, 2003.
[6] M. A. Alonso, B. David, and G. Richard, "Tempo and beat estimation of musical signals," Proceedings of the 5th International Conference on Music Information Retrieval (ISMIR 2004), Barcelona, Spain, 2004.
[7] J. A. Anderson, An Introduction to Neural Networks. MIT Press, 1995.
[8] J. P. Bello, L. Daudet, S. Abdallah, C. Duxbury, M. Davies, M. B. Sandler, and S.Member, "A tutorial on onset detection in music signals," IEEE Transactions on Speech and Audio Processing, Vol. 13, No. 5, pp. 1035-1047, 2005.
[9] L. Cohen, Time-frequency analysis: theory and applications. Prentice-Hall, Inc,1995.
[10] M. E. P. Davies and M. Plumbley, "Causal tempo tracking of audio," Proceedings of the 5th International Conference on Music Information Retrieval (ISMIR 2004), Barcelona, Spain, 2004.
[11] P. Delsarte and Y. V. Genin, "Establishing homologies in protein sequences," IEEE Transactions on Acoustics, Speech, and Signal Processing, Vol. ASSP-34, No. 3, 1986.
[12] S. Dixon, "Mirex 2006 audio beat tracking evaluation: Beatroot," Proceedings of the 2nd Music Information Retrieval Evaluation eXchange (MIREX 2006), 2006.
[13] J. Durbin, "The fitting of time series models," Revue de lInstitut International de Statistique 28, Vol. 28, pp. 233-243, 1960.
[14] D. P. Ellis, "Beat tracking with dynamic programming," Proceedings of the 2nd Music Information Retrieval Evaluation eXchange (MIREX 2006), 2006.
[15] L. Gu and K. Rose, "Perceptual harmonic cepstral coefficients as the front-end for speech recognition," Proceedings of the 6th International Conference on
Spoken Language Processing, Vol. 1, Beijing, China, pp. 309-312, 2000.
[16] S. Hainsworth and M. Macleod, "Beat tracking with particle filtering algorithms," Proceedings of IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA03), New Paltz, NY, 2003.
[17] J. S. R. Jang, "Audio signal processing and recognition." (in Chinese) available at the links for on-line courses at the author's homepage at http://neural.cs.nthu.edu.tw/jang.
[18] A. Klapuri, "Sound onset detection by applying psychoacoustic knowledge," Proceedings of IEEE International Conference on Acoustics, Speech and Signal
Processing (ICASSP99), 1999.
[19] S. Kumar, Neural Networks: A Classroom Approach. Tata Mcgraw Hill, 2004.
[20] L. I. Smith, "A tutorial on principal components analysis." http://csnet.otago.ac.nz/cosc453/student_tutorials/principal_components.pdf, 2002.
[21] A. Lacoste and D. Eck, "A supervised classification algorithm for note onset detection," EURASIP Journal on Advances in Signal Processing, Vol. 2007, No. 43745, p. 13, 2007.
[22] R. C. T. Lee, S. S. Tseng, R. C. Chang, and Y. T. Tsai, Introduction to the Design and Analysis of Algorithms. McGraw-Hill, 2005.
[23] K. Levenberg, "A method for the solution of certain non-linear problems in least squares," Quarterly of Applied Mathematics, Vol. 2, No. 2, pp. 164-168,1946.
[24] N. Levinson, "The wiener root-mean-square error criterion in klter design and prediction," Journal of Mathematics and Physics, Vol. 25, pp. 261-278, 1946.
[25] D. Marquardt, "An algorithm for the least-squares estimation of nonlinear parameters," SIAM Journal on Applied Mathematics, Vol. 11, No. 2, 1963.
[26] M. F. McKinney and D. Moelants, "Deviations from the resonance theory of tempo induction," Proceedings of the Conference on Interdisciplinary Musicology (CIM04), Graz, Austria, 2004.
[27] B. C. J. Moore, An Introduction to the Psychology of Hearing. New York: Academic Press, fifth ed., 1997.
[28] I. J. Nagrath, S. N. Sharan, R. Ranjan, and S.Kumar, Signals and Systems. Tata Mcgraw-Hill, first ed., 2001.
[29] G. Peeters, "Time variable tempo detection and beat marking," Proceedings of International Computer Music Conference (ICMC 2005), Barcelona, Spain, 2005.
[30] S. Roweis, "Levenberg-marquardt optimization." http://www.cs.toronto.edu/~roweis/notes.html.
[31] E. D. Scheirer, "Tempo and beat analysis of acoustic musical signals," The Journal of the Acoustical Society of America, Vol. 103, pp. 588-601, 1998.
[32] P. Scott, "Music classification using neural networks," Stanford University, 2001.
[33] G. Tzanetakis, "Tempo extraction using beat histograms," Proceedings of the 1th Music Information Retrieval Evaluation eXchange (MIREX 2005), 2005.
[34] J. Zurada, Introduction to artificial neural systems. West Publishing Co. St. Paul, MN, USA, 1995.
電子全文 Fulltext
本電子全文僅授權使用者為學術研究之目的,進行個人非營利性質之檢索、閱讀、列印。請遵守中華民國著作權法之相關規定,切勿任意重製、散佈、改作、轉貼、播送,以免觸法。
論文使用權限 Thesis access permission:校內立即公開,校外一年後公開 off campus withheld
開放時間 Available:
校內 Campus: 已公開 available
校外 Off-campus: 已公開 available


紙本論文 Printed copies
紙本論文的公開資訊在102學年度以後相對較為完整。如果需要查詢101學年度以前的紙本論文公開資訊,請聯繫圖資處紙本論文服務櫃台。如有不便之處敬請見諒。
開放時間 available 已公開 available

QR Code