Psychoacoustic Calibration of Loss Functions for Efficient End-to-End Neural Audio Coding

@article{Zhen2020PsychoacousticCO,
  title={Psychoacoustic Calibration of Loss Functions for Efficient End-to-End Neural Audio Coding},
  author={Kai Zhen and Mi Suk Lee and Jongmo Sung and Seung-Wha Beack and Minje Kim},
  journal={IEEE Signal Processing Letters},
  year={2020},
  volume={27},
  pages={2159-2163}
}
Conventional audio coding technologies commonly leverage human perception of sound, or psychoacoustics, to reduce the bitrate while preserving the perceptual quality of the decoded audio signals. For neural audio codecs, however, the objective nature of the loss function usually leads to suboptimal sound quality as well as high run-time complexity due to the large model size. In this work, we present a psychoacoustic calibration scheme to re-define the loss functions of neural audio coding… Expand

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