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. In this paper, a novel idea to enhance the estimation of the tempo in musical pieces is described, based on an 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%.
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