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import gradio as gr
import torch
from TTS.api import TTS
import os
# Get device
device = "cuda" if torch.cuda.is_available() else "cpu"
# Initialize TTS model
tts = TTS(model_name="voice_conversion_models/multilingual/vctk/freevc24", progress_bar=False).to(device)
def voice_conversion(input_audio, target_voice):
output_path = "output.wav"
# Perform voice conversion
tts.voice_conversion_to_file(source_wav=input_audio, target_wav=target_voice, file_path=output_path)
return output_path
# Get examples from Examples folder
examples_folder = "Examples/"
example_files = [f for f in os.listdir(examples_folder) if f.endswith(".wav")]
# Define Gradio Interface
with gr.Blocks() as demo:
gr.Markdown("## Voice Conversion using Coqui TTS")
with gr.Row():
input_audio = gr.Audio(source="microphone", label="Record or Upload Your Voice", type="filepath")
target_voice = gr.Dropdown(choices=example_files, label="Select Target Voice from Examples",
value=example_files[0], info="Located in Examples/ folder")
convert_button = gr.Button("Convert Voice")
output_audio = gr.Audio(label="Converted Voice", type="filepath")
with gr.Progress() as progress:
convert_button.click(voice_conversion, inputs=[input_audio, target_voice], outputs=output_audio,
progress=progress)
# Launch with public=True for public URL access and share link
demo.launch(share=True)
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