mrfakename commited on
Commit
1674465
1 Parent(s): 297e7ce

Update app.py

Browse files
Files changed (1) hide show
  1. app.py +5 -5
app.py CHANGED
@@ -12,8 +12,8 @@ for v in voicelist:
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  def synthesize(text, voice):
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  if text.strip() == "":
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  raise gr.Error("You must enter some text")
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- if len(text) > 500:
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- raise gr.Error("Text must be under 500 characters")
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  v = voice.lower()
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  return (24000, styletts2importable.inference(text, voices[v], alpha=0.3, beta=0.7, diffusion_steps=7, embedding_scale=1))
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  def clsynthesize(text, voice):
@@ -21,12 +21,12 @@ def clsynthesize(text, voice):
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  raise gr.Error("You must enter some text")
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  if len(text) > 500:
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  raise gr.Error("Text must be under 500 characters")
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- return (24000, styletts2importable.inference(text, styletts2importable.compute_style(voice), alpha=0.3, beta=0.7, diffusion_steps=7, embedding_scale=1))
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  def ljsynthesize(text):
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  if text.strip() == "":
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  raise gr.Error("You must enter some text")
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- if len(text) > 500:
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- raise gr.Error("Text must be under 500 characters")
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  noise = torch.randn(1,1,256).to('cuda' if torch.cuda.is_available() else 'cpu')
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  return (24000, ljspeechimportable.inference(text, noise, diffusion_steps=7, embedding_scale=1))
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  def synthesize(text, voice):
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  if text.strip() == "":
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  raise gr.Error("You must enter some text")
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+ if len(text) > 1500:
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+ raise gr.Error("Text must be under 1500 characters")
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  v = voice.lower()
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  return (24000, styletts2importable.inference(text, voices[v], alpha=0.3, beta=0.7, diffusion_steps=7, embedding_scale=1))
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  def clsynthesize(text, voice):
 
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  raise gr.Error("You must enter some text")
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  if len(text) > 500:
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  raise gr.Error("Text must be under 500 characters")
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+ return (24000, styletts2importable.inference(text, styletts2importable.compute_style(voice), alpha=0.3, beta=0.7, diffusion_steps=20, embedding_scale=1))
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  def ljsynthesize(text):
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  if text.strip() == "":
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  raise gr.Error("You must enter some text")
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+ if len(text) > 1500:
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+ raise gr.Error("Text must be under 1500 characters")
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  noise = torch.randn(1,1,256).to('cuda' if torch.cuda.is_available() else 'cpu')
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  return (24000, ljspeechimportable.inference(text, noise, diffusion_steps=7, embedding_scale=1))
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