Update tts.py
Browse files
tts.py
CHANGED
@@ -16,9 +16,15 @@ try:
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logging.info("Model and processor loaded successfully.")
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except Exception as e:
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logging.error(f"Error loading model or processor: {e}")
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def synthesize_speech(text):
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try:
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inputs = processor(text, return_tensors="pt")
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device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
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model.to(device)
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@@ -26,14 +32,18 @@ def synthesize_speech(text):
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with torch.no_grad():
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speech = model.generate(**inputs)
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logging.info("Speech generated successfully.")
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# Decode the generated speech and save to an audio file
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waveform = speech.cpu().numpy().flatten()
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# Convert waveform to audio format that Gradio can handle
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except Exception as e:
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logging.error(f"Error during speech synthesis: {e}")
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return None
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logging.info("Model and processor loaded successfully.")
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except Exception as e:
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logging.error(f"Error loading model or processor: {e}")
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raise
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def synthesize_speech(text):
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try:
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# Ensure text is not empty
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if not text.strip():
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logging.error("Text input is empty.")
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return None
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inputs = processor(text, return_tensors="pt")
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device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
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model.to(device)
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with torch.no_grad():
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speech = model.generate(**inputs)
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logging.info("Speech generated successfully.")
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# Decode the generated speech and save to an audio file
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waveform = speech.cpu().numpy().flatten()
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# Normalize waveform to the range [-1, 1]
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waveform = np.clip(waveform, -1.0, 1.0)
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# Convert waveform to audio format that Gradio can handle
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audio_path = "output.wav"
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sf.write(audio_path, waveform, 16000)
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return audio_path
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except Exception as e:
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logging.error(f"Error during speech synthesis: {e}")
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return None
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