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import os | |
from pathlib import Path | |
import gradio as gr | |
os.system('pip install .') | |
def greet(text, audio_file_path, progress=gr.Progress()): | |
text = "%s" % text | |
audio_file_path = "%s" % audio_file_path | |
out_path = Path("scripts/output/audio.wav") | |
progress(0.2, desc="Training voice embedding... (aprx 20 mins)") | |
os.system(f'python scripts/train.py --audio_path {audio_file_path}\ | |
--output_dir "models"') | |
progress(0.9, desc="Generating voice...") | |
os.system(f'python scripts/cloning_inference.py --model_path "models/microsoft_speecht5_tts_{Path(audio_file_path).stem}"\ | |
--input_text "{text}" --output_path "{str(out_path)}"') | |
return out_path | |
demo = gr.Interface( | |
fn=greet, | |
inputs=[gr.Textbox(label='What would you like the voice to say? (max. 2000 characters per request)'), | |
gr.Audio(type="filepath", source="upload", label='Upload a voice to clone (max. 50mb)')], | |
outputs="audio", | |
title="Deep Voice Cloning Tool" | |
) | |
demo.launch() | |