@inproceedings{aecd72ec2c934a3d96ed6e3f93b2fa1d,
title = "Extracting note onsets from musical recordings",
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 spectral energy flux. The proposed algorithm has a lower computational cost and incorporates 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.",
keywords = "Adaptive thresholding, Differentiator filter, Onset detection",
author = "Miguel Alonso and Gael Richard and Bertrand David",
year = "2005",
month = dec,
day = "1",
doi = "10.1109/ICME.2005.1521568",
language = "English",
isbn = "0780393325",
series = "IEEE International Conference on Multimedia and Expo, ICME 2005",
pages = "896--899",
booktitle = "IEEE International Conference on Multimedia and Expo, ICME 2005",
note = "IEEE International Conference on Multimedia and Expo, ICME 2005 ; Conference date: 06-07-2005 Through 08-07-2005",
}