Create voice_cloner.py

voice_cloner.py

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+from transformers import BarkModel, BarkProcessor
+import torch
+
+# You could switch to xtts-v2 or Tortoise if needed
+def clone_and_generate_text(text, reference_audio_path, output_path="clone_output.wav"):
+    processor = BarkProcessor.from_pretrained("suno/bark")
+    model = BarkModel.from_pretrained("suno/bark").cuda()
+
+    # Preprocess input
+    inputs = processor(text=text, voice_preset="v2/en_speaker_9", return_tensors="pt").to("cuda")
+
+    # Generate speech
+    speech = model.generate(**inputs)
+
+    # Save output
+    torchaudio.save(output_path, speech.cpu(), 22050)
+    return output_path