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E2-F5 TTS (zh_onnx)

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zh/F5-TTS-Faster/ckpts/vocos-mel-24khz/DS_Store ADDED
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zh/F5-TTS-Faster/ckpts/vocos-mel-24khz/README.md ADDED
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+ ---
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+ license: mit
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+ ---
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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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+
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+ [Audio samples](https://charactr-platform.github.io/vocos/) |
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+ Paper [[abs]](https://arxiv.org/abs/2306.00814) [[pdf]](https://arxiv.org/pdf/2306.00814.pdf)
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+
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+ Vocos is a fast neural vocoder designed to synthesize audio waveforms from acoustic features. Trained using a Generative
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+ Adversarial Network (GAN) objective, Vocos can generate waveforms in a single forward pass. Unlike other typical
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+ GAN-based vocoders, Vocos does not model audio samples in the time domain. Instead, it generates spectral
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+ coefficients, facilitating rapid audio reconstruction through inverse Fourier transform.
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+
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+ ## Installation
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+
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+ To use Vocos only in inference mode, install it using:
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+
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+ ```bash
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+ pip install vocos
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+ ```
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+
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+ If you wish to train the model, install it with additional dependencies:
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+
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+ ```bash
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+ pip install vocos[train]
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+ ```
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+
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+ ## Usage
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+
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+ ### Reconstruct audio from mel-spectrogram
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+
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+ ```python
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+ import torch
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+
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+ from vocos import Vocos
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+
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+ vocos = Vocos.from_pretrained("charactr/vocos-mel-24khz")
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+
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+ mel = torch.randn(1, 100, 256) # B, C, T
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+ audio = vocos.decode(mel)
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+ ```
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+
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+ Copy-synthesis from a file:
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+
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+ ```python
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+ import torchaudio
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+
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+ y, sr = torchaudio.load(YOUR_AUDIO_FILE)
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+ if y.size(0) > 1: # mix to mono
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+ y = y.mean(dim=0, keepdim=True)
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+ y = torchaudio.functional.resample(y, orig_freq=sr, new_freq=24000)
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+ y_hat = vocos(y)
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+ ```
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+
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+ ## Citation
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+
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+ If this code contributes to your research, please cite our work:
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+
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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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+ ```
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+
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+ ## License
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+
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+ The code in this repository is released under the MIT license.
zh/F5-TTS-Faster/ckpts/vocos-mel-24khz/config.yaml ADDED
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+ feature_extractor:
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+ class_path: vocos.feature_extractors.MelSpectrogramFeatures
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+ init_args:
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+ sample_rate: 24000
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+ n_fft: 1024
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+ hop_length: 256
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+ n_mels: 100
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+ padding: center
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+
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+ backbone:
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+ class_path: vocos.models.VocosBackbone
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+ init_args:
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+ input_channels: 100
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+ dim: 512
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+ intermediate_dim: 1536
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+ num_layers: 8
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+
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+ head:
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+ class_path: vocos.heads.ISTFTHead
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+ init_args:
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+ dim: 512
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+ n_fft: 1024
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+ hop_length: 256
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+ padding: center
zh/F5-TTS-Faster/ckpts/vocos-mel-24khz/pytorch_model.bin ADDED
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