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@@ -10,7 +10,7 @@ license: afl-3.0
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  ---
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  ## GroTTS Model
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- This model was trained with the [FastSpeech 2](https://arxiv.org/abs/2006.04558) architecture using approx. 2 hours of Gronings TTS dataset. For the best results you need to download the vocoder separately from [here](https://huggingface.co/ahnafsamin/parallelwavegan-gronings) and then use the following code:
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  ```
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  from espnet2.bin.tts_inference import Text2Speech
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  from scipy.io.wavfile import write
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  write("x.wav", 22050, output['wav'].numpy())
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  ```
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  ## TTS config
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  <details><summary>expand</summary>
 
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  ---
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  ## GroTTS Model
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+ This model was trained with the [FastSpeech 2](https://arxiv.org/abs/2006.04558) architecture using approx. 2 hours of Gronings TTS dataset. For the best results, you need to download the vocoder separately from [here](https://huggingface.co/ahnafsamin/parallelwavegan-gronings) and then use the following code:
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  ```
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  from espnet2.bin.tts_inference import Text2Speech
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  from scipy.io.wavfile import write
 
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  write("x.wav", 22050, output['wav'].numpy())
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  ```
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+ The GroTTS model is deployed [here](https://huggingface.co/spaces/ahnafsamin/GroTTS-FastSpeech2).
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+
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  ## TTS config
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  <details><summary>expand</summary>