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  TITLE
  Text to Speech Generalized End-To-End Loss for Speaker Verification, Real Time Voice Cloning
  
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  # 🌟 New model addition
  
  ## Model description
  Generalized End-To-End Loss for Speaker Verification implements Real time voice cloning, a way to generate a Text-To-Speech model adapted to a certain speaker with a short audio sample. The model implements the following paper.
  https://arxiv.org/pdf/1806.04558.pdf and the code is available on github.
  
  https://github.com/CorentinJ/Real-Time-Voice-Cloning
  
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  ## Open source status
  
  * [ ] the model implementation is available: (give details)
  https://colab.research.google.com/drive/1SUq5RLOI0TIMkrBzMHMms01aaVNgkO7c?usp=sharing
  
  The model can be run through Colaboratory. Here is an example of a generated voice.
  https://soundcloud.com/birger-mo-ll/generated-voice
  
  * [ ] the model weights are available: (give details)
  Here are the model weights that are used.
  
  encoder.load_model(project_name / Path("encoder/saved_models/pretrained.pt"))
  synthesizer = Synthesizer(project_name / Path("synthesizer/saved_models/logs-pretrained/taco_pretrained"))
  vocoder.load_model(project_name / Path("vocoder/saved_models/pretrained/pretrained.pt"))
  
  * [ ] who are the authors: @CorentinJ
  The author is not currently working on the repo, but since it is a fairly popular repo (25.000 stars) it might be reasonable to take the time to explore how to recreate / adapt the model to work with Huggingface transformer.
  
  
  