- Research Article
- Open access
- Published:
Accurate tempo estimation based on harmonic + noise decomposition
EURASIP Journal on Advances in Signal Processing volume 2007, Article number: 082795 (2006)
Abstract
We present an innovative tempo estimation system that processes acoustic audio signals and does not use any high-level musical knowledge. Our proposal relies on a harmonic + noise decomposition of the audio signal by means of a subspace analysis method. Then, a technique to measure the degree of musical accentuation as a function of time is developed and separately applied to the harmonic and noise parts of the input signal. This is followed by a periodicity estimation block that calculates the salience of musical accents for a large number of potential periods. Next, a multipath dynamic programming searches among all the potential periodicities for the most consistent prospects through time, and finally the most energetic candidate is selected as tempo. Our proposal is validated using a manually annotated test-base containing 961 music signals from various musical genres. In addition, the performance of the algorithm under different configurations is compared. The robustness of the algorithm when processing signals of degraded quality is also measured.
References
Alonso M, Badeau R, David B, Richard G: Musical tempo estimation using noise subspace projections. Proceedings of IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA '03), October 2003, New Paltz, NY, USA 95–98.
Alonso M, David B, Richard G: Tempo and beat estimation of musical signals. Proceedings of the 5th International Symposium on Music Information Retrieval (ISMIR '04), October 2004, Barcelona, Spain 158–163.
Alonso M, David B, Richard G: Tempo extraction for audio recordings. Proceedings of the 1st Annual Music Information Retrieval Evaluation eXchange (MIREX '05), September 2005, London, UK https://doi.org/www.music-ir.org/evaluation/mirex-results/audio-tempo/index.html
Alonso M, Richard G, David B: Extracting note onsets from musical recordings. Proceedings of IEEE International Conference on Multimedia & Expo (ICME '05), July 2005, Amsterdam, The Netherlands
Audio Tempo Extraction : Music Information Retrieval Evaluation eXchange. 2005.https://doi.org/www.music-ir.org/evaluation/mirex-results/audio-tempo/index.html
Badeau R: Méthodes à haute résolution pour l'estimation et le suivi de sinusöýdes modulées. Application aux signaux de musique, Ph.D. thesis. Télécom Paris, Paris, France; April 2005.
Badeau R, Boyer R, David B: EDS parametric modeling and tracking of audio signals. Proceedings of the 5th International Workshop on Digital Audio Effects (DAFx '02), September 2002, Hamburg, Germany 139–144.
Badeau R, David B, Richard G: Yet another subspace tracker. Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP '05), March 2005, Philadelphia, Pa, USA 4: 329–332.
Bello JP, Daudet L, Abdallah S, Duxbury C, Davies M, Sandler MB: A tutorial on onset detection in music signals. IEEE Transactions on Speech and Audio Processing 2005,13(5):1035–1046.
Desain P, Honing H: Computational models of beat induction: the rule based approach. Journal of New Music Research 1999,28(1):29–42. 10.1076/jnmr.28.1.29.3123
Dvornikov M: Formulae of numerical differentiation. 2003.https://doi.org/arxiv.org/abs/math.NA/0306092
Foote J, Uchihashi S: The beat spectrum: a new approach to rhythm analysis. Proceedings of the IEEE International Conference on Multimedia and Expo (ICME '01), August 2001, Tokyo, Japan 881–884.
Gillet O, Richard G: Extraction and remixing of drum tracks from polyphonic music signals. Proceedings of IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA '05), October 2005, New Paltz, NY, USA 315–318.
Goto M, Muraoka Y: Issues in evaluating beat tracking systems. Proceedings of the 15th International Joint Conference on Artificial Intelligence (IJCAI '97), August 1997, Nagoya, Japan 9–16.
Goto M, Muraoka Y: Real-time rhythm tracking for drumless audio signals. Proceedings of the 15th International Joint Conference on Artificial Intelligence (IJCAI '97), August 1997, Nagoya, Japan 135–144.
Goto M, Muraoka Y: Music understanding at the beat level: real-time beat tracking for audio signals. In Computational Auditory Scene Analysis. Lawrence Erlbaum Associates, Mahwah, NJ, USA; 1998:157–176.
Gouyon F: Quantitative comparison of tempo induction algorithms. https://doi.org/www.iua.upf.es/mtg/ismir2004/contest/tempoContest/node3.html
Gouyon F, Herrera P, Cano P: Pulse-dependent analyses of percussive music. Proceedings of AES22 International Conference on Virtual, Synthetic and Entertainment Audio, June 2002, Espoo, Finland
Gouyon F, Klapuri A, Dixon S, et al.: An experimental comparison of audio tempo induction algorithms. IEEE Transactions on Speech and Audio Processing 2006.,14(5):
Hainsworth S: Techniques for the automated analysis of musical audio, Ph.D. thesis. Department of Engineering, Cambridge University, Cambridge, UK; December 2003.
Hainsworth S, Macleod M: Beat tracking with particle filtering algorithms. Proceedings of IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA '03), October 2003, New Paltz, NY, USA 91–94.
Hermus K, Wambacq P: Assessment of signal subspace based speech enhancement for noise robust speech recognition. Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP '04), May 2004, Montreal, Quebec, Canada 1: I945–I948.
Jehan T: Event-synchronous music analysis/synthesis. Proceedings of the International Conference on Digital Audio Effects (DAFx '04), October 2004, Naples, Italy
Jensen K, Andersen T: Beat estimation on the beat. Proceedings of the IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA '03), October 2003, New Paltz, NY, USA 87–90.
Klapuri A: Sound onset detection by applying psychoacoustic knowledge. Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP '99), March 1999, Phoenix, Ariz, USA 6: 3089–3092.
Klapuri A, Eronen A, Astola J: Automatic estimation of the meter of acoustic musical signals. IEEE Transactions on Speech and Audio Processing 2006.,14(1):
Laroche J: Efficient tempo and beat tracking in audio recordings. Journal of the Audio Engineering Society 2003,51(4):226–233.
Lerdahl F, Jackendoff R: A Generative Theory of Tonal Music. MIT Press, Cambridge, Mass, USA; 1983.
Meddis R: Simulation of auditory-neural transduction: further studies. The Journal of the Acoustical Society of America 1988,83(3):1056–1063. 10.1121/1.396050
Moelants D: Preferred tempo reconsidered. Proceedings of the 7th International Conference on Music Perception and Cognition, July 2002, Sydney, Australia 580–583.
Moore B (Ed): Hearing. 2nd edition. Academic Press, London, UK; 1995.
Parncutt R: A perceptual model of pulse salience and metrical accent in musical rhythms. Music Perception 1994,11(4):409–464.
Peeters G: Time variable tempo detection and beat marking. Proceedings of the International Computer Music Conference (ICMC '05), September 2005, Barcelona, Spain
Rabiner L, Juang B: Fundamentals of Speech Recognition. Prentice Hall PTR, Englewood Cliffs, NJ, USA; 1993.
Raphael C: Automatic segmentation of acoustic musical signals using hidden Markov models. IEEE Transactions on Pattern Analysis and Machine Intelligence 1999,21(4):360–370. 10.1109/34.761266
Scheirer ED: Tempo and beat analysis of acoustic musical signals. The Journal of the Acoustical Society of America 1998,103(1):588–601. 10.1121/1.421129
Schwartz D: Méthodes Statistiques à l'Usage des Médecins et des Biologistes, Flammarion Medecine Series. 3rd edition. Flammarion, Paris, France; 1963.
Seppänen J: Tatum grid analysis of musical signals. Proceedings of IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA '01), October 2001, New Paltz, NY, USA 131–134.
Serra X: A system for sound analysis/transformation/synthesis based on a deterministic plus stochastic decomposition, Ph.D. thesis. Stanford University, Stanford, Calif, USA; 1989.
Sethares WA, Morris RD, Sethares JC: Beat tracking of musical performances using low-level audio features. IEEE Transactions on Speech and Audio Processing 2005,13(2):275–285.
Sethares WA, Staley T: Meter and periodicity in musical performance. Journal of New Music Research 2001,30(2):149–158. 10.1076/jnmr.30.2.149.7111
Temperley D: An evaluation system for metrical models. Computer Music Journal 2004,28(3):28–44. 10.1162/0148926041790621
Tzanetakis G, Cook P: Musical genre classification of audio signals. IEEE Transactions on Speech and Audio Processing 2002,10(5):293–302. 10.1109/TSA.2002.800560
Vaidyanathan P: Multirate Systems and Filter Banks. Prentice-Hall PTR, Englewood Cliffs, NJ, USA; 1992.
Wang J-F, Yang C-H, Chang K-H: Subspace tracking for speech enhancement in car noise environments. Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP '04), May 2004, Montreal, Quebec, Canada 2: 789–792.
Wax M, Kailath T: Detection of signals by information theoretic criteria. IEEE Transactions on Acoustics, Speech, and Signal Processing 1985,33(2):387–392. 10.1109/TASSP.1985.1164557
Zhao LC, Krishnaiah PR, Bai ZD: On detection of the number of signals in presence of white noise. Journal of Multivariate Analysis 1986,20(1):1–25. 10.1016/0047-259X(86)90017-5
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
Open Access This article is distributed under the terms of the Creative Commons Attribution 2.0 International License ( https://creativecommons.org/licenses/by/2.0 ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
About this article
Cite this article
Alonso, M., Richard, G. & David, B. Accurate tempo estimation based on harmonic + noise decomposition. EURASIP J. Adv. Signal Process. 2007, 082795 (2006). https://doi.org/10.1155/2007/82795
Received:
Revised:
Accepted:
Published:
DOI: https://doi.org/10.1155/2007/82795