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Template-Based Estimation of Time-Varying Tempo
EURASIP Journal on Advances in Signal Processing volume 2007, Article number: 067215 (2006)
We present a novel approach to automatic estimation of tempo over time. This method aims at detecting tempo at the tactus level for percussive and nonpercussive audio. The front-end of our system is based on a proposed reassigned spectral energy flux for the detection of musical events. The dominant periodicities of this flux are estimated by a proposed combination of discrete Fourier transform and frequency-mapped autocorrelation function. The most likely meter, beat, and tatum over time are then estimated jointly using proposed meter/beat subdivision templates and a Viterbi decoding algorithm. The performances of our system have been evaluated on four different test sets among which three were used during the ISMIR 2004 tempo induction contest. The performances obtained are close to the best results of this contest.
Bilmes J: Timing is of the essence: perceptual and computational techniques for representing, learning, and reproducing expressive timing in percussive rhythm, M.S. thesis.
Klapuri A, Eronen A, Astola J: Analysis of the meter of acoustical musical signals. IEEE Transactions on Audio, Speech and Language Processing 2006,14(1):342–355.
Gouyon F: A computational approach to rhythm description, Ph.D. thesis. Universitat Pompeu Fabra, Barcelona, Spain; 2005.
Gouyon F, Dixon S: A review of automatic rhythm description systems. Computer Music Journal 2005,29(1):34–54. 10.1162/comj.2005.29.1.34
Brown JC: Determination of the meter of musical scores by autocorrelation. Journal of the Acoustical Society of America 1993,94(4):1953–1957. 10.1121/1.407518
Allen P, Dannenberg R: Tracking musical beats in real time. Proceedings of the International Computer Music Conference and International Computer Music Association, September 1990, San Francisco, Calif, USA 140–143.
Klapuri A: Sound onset detection by applying psychoacoustic knowledge. Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP '99), March 1999, Phoenix, Ariz, USA 6: 3089–3092.
Gouyon F, Herrera P, Cano P: Pulse-dependent analyses of percussive music. Proceedings of AES 22nd International Conference on Virtual, Synthetic and Entertainment Audio, June 2002, Espoo, Finland 396–401.
Bello J: Towards the automated analysis of simple polyphonic music: a knowledge based approach, Ph.D. thesis. Queen Mary University of London, London, UK; 2003.
Uhle C, Herre J: Estimation of tempo, micro time and time signature from percussive music. Proceedings of the 6th International Conference on Digital Audio Effects (DAFx '03), September 2003, London, UK 84–89.
Goto M: An audio-based real-time beat tracking system for music with or without drum-sounds. Journal of New Music Research 2001,30(2):159–171. 10.1076/jnmr.18.104.22.16814
Scheirer ED: Tempo and beat analysis of acoustic musical signals. Journal of the Acoustical Society of America 1998,103(1):588–601. 10.1121/1.421129
Paulus J, Klapuri A: Measuring the similarity of rhythmic patterns. Proceedings of the 3rd International Conference on Music Information Retrieval (ISMIR '02), October 2002, Paris, France 150–156.
Dixon S: Automatic extraction of tempo and beat from expressive performances. Journal of New Music Research 2001,30(1):39–58. 10.1076/jnmr.22.214.171.12419
Brown JC, Puckette MS: Calculation of a "narrowed" autocorrelation function. Journal of the Acoustical Society of America 1989,85(4):1595–1601. 10.1121/1.397363
Gouyon F, Herrera P: Determination of the meter of musical audio signals: seeking recurrences in beat segment descriptors. Proceedings of the 114th Convention of Audio Engineering Society (AES '03), March 2003, Amsterdam, The Netherlands
Laroche J: Efficient tempo and beat tracking in audio recordings. Journal of the Audio Engineering Society 2003,51(4):226–233.
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):1832–1844.
Harris FJ: On the use of windows for harmonic analysis with the discrete Fourier transform. Proceedings of the IEEE 1978,66(1):51–83.
Flandrin P: Time-Frequency/Time-Scale Analysis. Academic Press, San Diego, Calif, USA; 1999.
Peeters G, Rodet X: Sinola: a new analysis/synthesis using spectrum peak shape distortion, phase and reassigned spectrum. Proceedings of the International Computer Music Conference (ICMC '99), October 1999, Beijing, China 153–156.
Peeters G: Modèles et modélisation du signal sonore adaptés à ses caractéristiques locales, Ph.D. thesis. Université Paris VI, Paris, France; 2001.
Röbel A: A new approach to transient processing in the phase vocoder. Proceedings of the 6th International Conference on Digital Audio Effects (DAFx '03), September 2003, London, UK 344–349.
Hainsworth S, Wolfe P: Time-frequency reassignment for music analysis. Proceedings of International Computer Music Conference (ICMC '01), September 2001, La Habana, Cuba 14–17.
Maher R, Beauchamp J: Fundamental frequency estimation of musical signals using a two-way mismatch procedure. Journal of the Acoustical Society of America 1994,95(4):2254–2263. 10.1121/1.408685
Doval B, Rodet X: Fundamental frequency estimation and tracking using maximum likelihood harmonic matching and HMMs. Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP '93), April 1993, Minneapolis, Minn, USA 1: 221–224.
Peeters G: Music pitch representation by periodicity measures based on combined temporal and spectral representations. Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP '06), May 2006, Toulouse, France 53–56.
Viterbi A: Error bounds for convolutional codes and an asymptotically optimum decoding algorithm. IEEE Transactions on Information Theory 1967,13(2):260–269.
Rabiner LR: Tutorial on hidden Markov models and selected applications in speech recognition. Proceedings of the IEEE 1989,77(2):257–286. 10.1109/5.18626
Peeters G: Rhythm classification using spectral rhythm patterns. Proceedings of the 6th International Conference on Music Information Retrieval (ISMIR '05), September 2005, London, UK 644–647.
Dixon S, Pampalk E, Widmer G: Classification of dance music by periodicity patterns. Proceedings of the 4th International Conference on Music Information Retrieval (ISMIR '03), October 2003, Baltimore, Md, USA 159–165.
Vinet H: The Semantic Hifi project. Proceedings of the International Computer Music Conference (ICMC '05), September 2005, Barcelona, Spain 503–506.
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Peeters, G. Template-Based Estimation of Time-Varying Tempo. EURASIP J. Adv. Signal Process. 2007, 067215 (2006). https://doi.org/10.1155/2007/67215
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