EXTRACTING NOTE ONSETS FROM MUSICAL RECORDINGS (WedPmOR5)

Author(s) : Miguel Alonso (ENST - Télécom Paris, France) Gaël Richard (ENST - Télécom Paris, France) Bertrand David (ENST - Télécom Paris, France)

Abstract : Automatic temporal segmentation of music signals into note onsets is central for a large number of audio applications. In this paper, we present a variation of a previously existing note onset detection method, based on the so-called the spectral energy flux. The proposed changes have a low computational cost and lead to a more accurate estimation of the frequency content derivative, yielding better results for a wide range of music signals. The performance of the system was validated using a database of musical recordings containing 670 note onsets. This database was hand-labeled and cross validated by three annotators. Comparisons to previous work are also presented along with possible directions of future research.

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