AUDASCITY: AUdio denoising by adaptive social CosparsITY

AUDASCITY: AUdio denoising by adaptive social CosparsITY. Gaultier, C., Kitić, S., Bertin, N., & Gribonval, R. In 2017 25th European Signal Processing Conference (EUSIPCO), pages 1265-1269, Aug, 2017.

Paper doi abstract bibtex

This work aims at introducing a new algorithm, AUDASCITY, and comparing its performance to the time-frequency block thresholding algorithm for the ill-posed problem of audio denoising. We propose a heuristics which combines time-frequency structure, cosparsity, and an adaptive scheme to denoise audio signals corrupted with white noise. We report that AUDASCITY outperforms state-of-the-art for each numerical comparison. While there is still room for some perceptual improvements, AUDASCITY's usefulness is shown when used as a front-end for a classification task.

@InProceedings{8081411,
  author = {C. Gaultier and S. Kitić and N. Bertin and R. Gribonval},
  booktitle = {2017 25th European Signal Processing Conference (EUSIPCO)},
  title = {AUDASCITY: AUdio denoising by adaptive social CosparsITY},
  year = {2017},
  pages = {1265-1269},
  abstract = {This work aims at introducing a new algorithm, AUDASCITY, and comparing its performance to the time-frequency block thresholding algorithm for the ill-posed problem of audio denoising. We propose a heuristics which combines time-frequency structure, cosparsity, and an adaptive scheme to denoise audio signals corrupted with white noise. We report that AUDASCITY outperforms state-of-the-art for each numerical comparison. While there is still room for some perceptual improvements, AUDASCITY's usefulness is shown when used as a front-end for a classification task.},
  keywords = {audio signal processing;compressed sensing;signal denoising;time-frequency analysis;white noise;time-frequency structure;adaptive scheme;audio signals;audio denoising;AUDASCITY;time-frequency block thresholding algorithm;white noise;adaptive social cosparsity;Noise reduction;Time-frequency analysis;Signal to noise ratio;Signal processing algorithms;Computational modeling},
  doi = {10.23919/EUSIPCO.2017.8081411},
  issn = {2076-1465},
  month = {Aug},
  url = {https://www.eurasip.org/proceedings/eusipco/eusipco2017/papers/1570347077.pdf},
}

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