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--- |
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language: "de" |
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inference: false |
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tags: |
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- Vocoder |
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- HiFIGAN |
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- text-to-speech |
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- TTS |
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- speech-synthesis |
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- speechbrain |
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license: "apache-2.0" |
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datasets: |
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- custom |
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--- |
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# Vocoder with HiFIGAN trained on custom German dataset |
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This repository provides all the necessary tools for using a [HiFIGAN](https://arxiv.org/abs/2010.05646) vocoder trained on a generated German dataset using [mp3_to_training_data](https://github.com/padmalcom/mp3_to_training_data). |
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The pre-trained model (8 epochs so far) takes in input a spectrogram and produces a waveform in output. Typically, a vocoder is used after a TTS model that converts an input text into a spectrogram. |
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## How to use |
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Install speechbrain. |
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```bash |
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pip install speechbrain |
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``` |
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Use a TTS model (e.g. [tts-tacotron-german](https://huggingface.co/padmalcom/tts-tacotron2-german)), generate a spectrogram and convert it to audio. |
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```python |
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import torchaudio |
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from speechbrain.pretrained import Tacotron2 |
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from speechbrain.pretrained import HIFIGAN |
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tacotron2 = Tacotron2.from_hparams(source="padmalcom/tts-tacotron2-german", savedir="tmpdir_tts") |
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hifi_gan = HIFIGAN.from_hparams(source="padmalcom/tts-hifigan-german", savedir="tmpdir_vocoder") |
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mel_output, mel_length, alignment = tacotron2.encode_text("Mary had a little lamb") |
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waveforms = hifi_gan.decode_batch(mel_output) |
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torchaudio.save('example_TTS.wav',waveforms.squeeze(1), 22050) |
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``` |
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### Inference on GPU |
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To perform inference on the GPU, add `run_opts={"device":"cuda"}` when calling the `from_hparams` method. |
