@inproceedings{06067592cb2a47be8fc9a90d5b672e81,
title = "Musical tempo estimation using noise subspace projections",
abstract = "Tempo estimation plays a fundamental role in music analysis, especially for the automatic processing of large amounts of musical data. A novel idea to enhance the estimation of the tempo in musical pieces is described, based on a harmonic/noise decomposition. This separation of the signal into a deterministic and a stochastic part is performed by projecting the signal onto its noise subspace. Besides, the proposed algorithm shares various elements with other tempo estimation methods. On a database composed of 54 excerpts from many musical genres, our algorithm scored a success rate of 96\%.",
keywords = "Databases, Frequency estimation, Image analysis, Instruments, Machine assisted indexing, Multiple signal classification, Rhythm, Signal analysis, Signal processing, Stochastic resonance",
author = "M. Alonso and R. Badeau and B. David and G. Richard",
note = "Publisher Copyright: {\textcopyright} 2003 IEEE.; IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, WASPAA 2003 ; Conference date: 19-10-2003 Through 22-10-2003",
year = "2003",
month = jan,
day = "1",
doi = "10.1109/ASPAA.2003.1285828",
language = "English",
series = "IEEE Workshop on Applications of Signal Processing to Audio and Acoustics",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "95--98",
booktitle = "2003 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics Proceedings, WASPAA 2003",
}