Musical tempo estimation using noise subspace projections

Miguel Alonso Arevalo (1) , Roland Badeau (1) , Bertrand David (1) , Gael Richard (1)

1 LTCI - Laboratoire Traitement et Communication de l'Information

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%.

Domaines: Traitement du signal et de l'image [eess.SP]; Traitement du signal et de l'image [eess.SP]

Miguel Alonso Arevalo, Roland Badeau, Bertrand David, Gael Richard. Musical tempo estimation using noise subspace projections. Proc. of IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA), 2003, New Paltz, New York, United States. pp.95--98. ⟨hal-00945267⟩