《Image2Reverb: Cross-Modal Reverb Impulse Response Synthesis》(2021)

Related tags

Deep Learningimage2reverb
Overview

Image2Reverb

Image2Reverb is an end-to-end neural network that generates plausible audio impulse responses from single images of acoustic environments. Code for the paper Image2Reverb: Cross-Modal Reverb Impulse Response Synthesis. The architecture is a conditional GAN with a ResNet50 (pre-trained on Places365 and fine-tuned) image encoder. It generates monoaural audio impulse responses (directly applicable to convolution applications) as magnitude spectrograms.

Dependencies

Model/Data:

  • PyTorch>=1.7.0
  • PyTorch Lightning
  • torchvision
  • torchaudio
  • librosa
  • PyRoomAcoustics
  • PIL

Eval/Preprocessing:

  • PySoundfile
  • SciPy
  • Scikit-Learn
  • python-acoustics
  • google-images-download
  • matplotlib

Usage

We will make a pre-trained model available soon!

Acknowledgments

We borrow and adapt code snippets from GANSynth (and this PyTorch re-implementation), additional snippets from this PGGAN implementation, and more.

Owner
Nikhil Singh
Nikhil Singh
GitHub Repository
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