M. D. V. M. da Costa and L. W. P. Biscainho, “The Fast Local Sparsity Method: A Low-Cost Combination of Time-Frequency Representations Based on the Hoyer Sparsity,” J. Audio Eng. Soc., vol. 70, no. 9, pp. 698–707, Sep. 2022, doi: 10.17743/jaes.2022.0036.
da Costa MDVM, Biscainho LWP. The Fast Local Sparsity Method: A Low-Cost Combination of Time-Frequency Representations Based on the Hoyer Sparsity. J Audio Eng Soc. 2022;70(9):698-707. doi:10.17743/jaes.2022.0036
@article{daCosta2022_21889,
author = {da Costa, Maurício do V. M. and Biscainho, Luiz W. P.},
title = {{The Fast Local Sparsity Method: A Low-Cost Combination of Time-Frequency Representations Based on the Hoyer Sparsity}},
journal = {Journal of the Audio Engineering Society},
volume = {70},
number = {9},
pages = {698--707},
year = {2022},
month = sep,
publisher = {Audio Engineering Society},
doi = {10.17743/jaes.2022.0036},
url = {https://doi.org/10.17743/jaes.2022.0036}
}
TY - JOUR
TI - The Fast Local Sparsity Method: A Low-Cost Combination of Time-Frequency Representations Based on the Hoyer Sparsity
AU - da Costa, Maurício do V. M.
AU - Biscainho, Luiz W. P.
T2 - Journal of the Audio Engineering Society
J2 - J. Audio Eng. Soc.
VL - 70
IS - 9
SP - 698
EP - 707
PY - 2022
DA - 2022/09/06
DO - 10.17743/jaes.2022.0036
UR - https://doi.org/10.17743/jaes.2022.0036
PB - Audio Engineering Society
LA - en
AB - This paper describes a novel, low-cost method for combining time-frequency representations into a more sparse one. To this end, a new local quality measure that is based on an amplitude-weighted version of the so-called Hoyer sparsity is proposed. A detailed evaluation procedure that employs a dataset with nearly perfect f0 annotations of melodic signals and a set of white-noise pulses is adopted for assessing the time-frequency resolution attained. The proposed method is shown to produce state-of-the-art results among the existing combination methods in terms of energy concentration at frequency contours, onsets, and offsets, meeting the most desirable requirements: high time-frequency resolution, low computational cost, and the capability of combining representations with non-linear frequency scale.
ER -