Update app.py
Browse files
app.py
CHANGED
@@ -129,7 +129,7 @@ def make_npz_prompt(name, uploaded_audio, recorded_audio, transcript_content):
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clear_prompts()
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audio_prompt = uploaded_audio if uploaded_audio is not None else recorded_audio
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sr, wav_pr = audio_prompt
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-
if len(wav_pr) / sr >
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return "Rejected, Audio too long (should be less than 15 seconds)", None
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if not isinstance(wav_pr, torch.FloatTensor):
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wav_pr = torch.FloatTensor(wav_pr)
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@@ -190,7 +190,7 @@ def infer_from_audio(text, language, accent, audio_prompt, record_audio_prompt,
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else:
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audio_prompt = audio_prompt if audio_prompt is not None else record_audio_prompt
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sr, wav_pr = audio_prompt
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-
if len(wav_pr) / sr >
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return "Rejected, Audio too long (should be less than 15 seconds)", None
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if not isinstance(wav_pr, torch.FloatTensor):
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wav_pr = torch.FloatTensor(wav_pr)
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clear_prompts()
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audio_prompt = uploaded_audio if uploaded_audio is not None else recorded_audio
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sr, wav_pr = audio_prompt
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+
if len(wav_pr) / sr > 60*6:
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return "Rejected, Audio too long (should be less than 15 seconds)", None
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if not isinstance(wav_pr, torch.FloatTensor):
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wav_pr = torch.FloatTensor(wav_pr)
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else:
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audio_prompt = audio_prompt if audio_prompt is not None else record_audio_prompt
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sr, wav_pr = audio_prompt
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+
if len(wav_pr) / sr > 60*6:
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return "Rejected, Audio too long (should be less than 15 seconds)", None
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if not isinstance(wav_pr, torch.FloatTensor):
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wav_pr = torch.FloatTensor(wav_pr)
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