Spaces:
Running
Running
File size: 1,476 Bytes
068b7da 609ffca 068b7da 609ffca 068b7da c92f138 068b7da 9572287 068b7da 95540a0 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 |
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)
# Get examples from Examples folder
examples_folder = "Examples/"
example_files = [f for f in os.listdir(examples_folder) if f.endswith(".wav")]
def voice_conversion(input_audio, target_voice):
output_path = "output.wav"
# Perform voice conversion
target_voice = f"{examples_folder}{target_voice}"
print(f"Target voice is: {target_voice}")
tts.voice_conversion_to_file(source_wav=input_audio, target_wav=target_voice, file_path=output_path)
return output_path
# Define Gradio Interface
with gr.Blocks() as demo:
gr.Markdown("## Voice Conversion using Coqui TTS")
with gr.Row():
input_audio = gr.Audio(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")
convert_button.click(voice_conversion, inputs=[input_audio, target_voice], outputs=output_audio)
# Launch with public=True for public URL access and share link
demo.launch(share=True)
|