File size: 3,247 Bytes
068b7da 6d72e83 cd428c2 068b7da 6d72e83 609ffca 6d72e83 cd428c2 068b7da 6d72e83 068b7da 6d72e83 068b7da 6d72e83 068b7da c92f138 e185191 068b7da 6d72e83 068b7da 6d72e83 e185191 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 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 |
import gradio as gr
import torch
from TTS.api import TTS
import os
import librosa
from datetime import datetime
# 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 convert_audio_to_wav(file_path):
"""Convert any supported format (mp3, etc.) to wav using librosa"""
output_path = "temp_input.wav"
audio, sr = librosa.load(file_path, sr=None) # Load file (wav, mp3, etc.)
librosa.output.write_wav(output_path, audio, sr) # Convert to wav
return output_path
def voice_conversion(input_audio, target_voice, uploaded_target_voice):
print(datetime.now())
output_path = "output.wav"
# Check if the user uploaded a target voice, otherwise use selected from examples
if uploaded_target_voice is not None:
target_voice_path = uploaded_target_voice
# Convert uploaded target to wav if necessary
if not uploaded_target_voice.endswith(".wav"):
target_voice_path = convert_audio_to_wav(uploaded_target_voice)
else:
target_voice_path = os.path.join("Examples", target_voice)
if not os.path.exists(target_voice_path):
return "Error: Target voice file not found."
# Convert input audio to wav if necessary
if not input_audio.endswith(".wav"):
input_audio = convert_audio_to_wav(input_audio)
# Perform voice conversion
tts.voice_conversion_to_file(source_wav=input_audio, target_wav=target_voice_path, 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(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"
)
uploaded_target_voice = gr.Audio(
label="Or Upload Your Own Target Voice",
type="filepath"
)
with gr.Row():
play_button = gr.Button("Preview Selected Target Voice")
preview_audio = gr.Audio(label="Preview Target Voice", type="filepath")
# Add convert button and output audio
convert_button = gr.Button("Convert Voice")
output_audio = gr.Audio(label="Converted Voice", type="filepath")
# Preview button for listening to the selected target voice from examples
def preview_target_voice(selected_target_voice):
return os.path.join(examples_folder, selected_target_voice)
play_button.click(preview_target_voice, inputs=[target_voice], outputs=preview_audio)
# Conversion process
convert_button.click(
voice_conversion,
inputs=[input_audio, target_voice, uploaded_target_voice],
outputs=output_audio
)
# Launch with public=True for public URL access and share link
demo.launch(share=True)
|