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Home »Research Projects »Neural Feature Predictor and Discriminative Residual Coding

Neural Feature Predictor and Discriminative Residual Coding

Paper

Haici Yang, Wootaek Lim, and Minje Kim, “Neural Feature Predictor and Discriminative Residual Coding for Low-Bitrate Speech Coding,” in Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP) 2023 [arXiv] (under review)

Source codes

https://github.com/haiciyang/Feature-predictor-for-speech-codec

Audio examples

genc_samples-1Download

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  • Home
  • News
  • People
  • Research Projects
    • Personalized Speech Enhancement
      • Collaborative Deep Learning
      • Sparse Mixture of Local Experts
      • Knowledge Distillation for PSE
      • Self-Supervised Learning and Data Purification for PSE
    • Music Applications
      • Neural Pitch Correction of Singing Voice
      • SpaIn-Net: Spatially Informed Music Source Separation
      • Don’t Separate, Learn to Remix: End-to-End Neural Remixing
      • Neural Upmixing via Style Transfer
    • Learning to Hash for Source Separation
    • Neural Audio Coding
      • Psychoacoustic Loss Functions for Neural Audio Coding
      • Source-Aware Neural Audio Coding
      • HARP-Net
    • Collaborative Audio Enhancement
  • Publication
  • Prospective Members
  • QuickFacts