---
license: mit
library: ONNX
base_model: charactr/vocos-mel-24khz
---

**Vocos: Closing the gap between time-domain and Fourier-based neural vocoders for high-quality audio synthesis**

**Audio samples | Paper [abs] [pdf]**

Vocos is a fast neural vocoder designed to synthesize audio waveforms from acoustic features. Trained using a Generative Adversarial Network (GAN) objective, Vocos can generate waveforms in a single forward pass. Unlike other typical GAN-based vocoders, Vocos does not model audio samples in the time domain. Instead, it generates spectral coefficients, facilitating rapid audio reconstruction through inverse Fourier transform.

This is a ONNX version of the original 24khz mel spectrogram [model](https://huggingface.co/charactr/vocos-mel-24khz). The model predicts spectrograms and the ISTFT is performed outside ONNX as ISTFT is still not implemented as an operator in ONNX.

## Usage

Try out in colab:

<a target="_blank" href="https://colab.research.google.com/drive/1J1tWd56D7CPwmVCP-pbMNzlRWYvlyADN">
  <img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/>
</a>

## Citation

```
@article{siuzdak2023vocos,
  title={Vocos: Closing the gap between time-domain and Fourier-based neural vocoders for high-quality audio synthesis},
  author={Siuzdak, Hubert},
  journal={arXiv preprint arXiv:2306.00814},
  year={2023}
}

```