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--- |
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license: mit |
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library: ONNX |
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base_model: charactr/vocos-mel-24khz |
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--- |
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**Vocos: Closing the gap between time-domain and Fourier-based neural vocoders for high-quality audio synthesis** |
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**Audio samples | Paper [abs] [pdf]** |
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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. |
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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. |
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## Usage |
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Try out in colab: |
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<a target="_blank" href="https://colab.research.google.com/drive/1J1tWd56D7CPwmVCP-pbMNzlRWYvlyADN"> |
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<img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/> |
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</a> |
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## Citation |
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``` |
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@article{siuzdak2023vocos, |
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title={Vocos: Closing the gap between time-domain and Fourier-based neural vocoders for high-quality audio synthesis}, |
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author={Siuzdak, Hubert}, |
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journal={arXiv preprint arXiv:2306.00814}, |
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year={2023} |
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} |
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``` |
