Audio Style Transfer

@article{Grinstein2018AudioST,
  title={Audio Style Transfer},
  author={Eric Grinstein and Ngoc Q. K. Duong and A. Ozerov and P. P{\'e}rez},
  journal={2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
  year={2018},
  pages={586-590}
}
“Style transfer” among images has recently emerged as a very active research topic, fuelled by the power of convolution neural networks (CNNs), and has become fast a very popular technology in social media. This paper investigates the analogous problem in the audio domain: How to transfer the style of a reference audio signal to a target audio content? We propose a flexible framework for the task, which uses a sound texture model to extract statistics characterizing the reference audio style… Expand
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  • R. Saldaña, G. Mendizabal-Ruiz
  • Computer Science
  • 2020 17th International Conference on Electrical Engineering, Computing Science and Automatic Control (CCE)
  • 2020
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