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. 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:
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}
}