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import numpy as np
import torch
import gradio as gr
from TTS.api import TTS # Import TTS library
# Placeholder for model loading and voice cloning logic
class VoiceCloner:
def __init__(self):
self.model = None
self.tts = None
def load_model(self, npz_file):
data = np.load(npz_file)
# Load your model parameters from the npz file
# Initialize your model here with the loaded parameters
self.model = data # Example; replace with your actual model loading code
def clone_voice(self, audio_file):
# Implement the logic to clone voice from the uploaded audio file
return audio_file # Placeholder; return processed audio
def load_tts_model(self):
# Load a pretrained TTS model
self.tts = TTS(model_name="tts_models/en/ljspeech/glow-tts") # You can choose a different model if needed
def text_to_speech(self, text):
# Use the loaded TTS model to convert text to speech
if self.tts is not None:
output_audio = self.tts.tts(text)
return output_audio # Return the generated audio
else:
return "TTS model not loaded!"
# Create the Gradio interface
def create_interface():
cloner = VoiceCloner()
with gr.Blocks() as demo:
gr.Markdown("## Voice Cloning and TTS Application")
# User uploads their .npz file
npz_file = gr.File(label="Upload Your .npz Voice Model")
audio_input = gr.Audio(source="upload", type="filepath", label="Upload Original Audio")
text_input = gr.Textbox(label="Text Input for TTS")
output_audio = gr.Audio(label="Cloned Voice Output or TTS Output")
upload_button = gr.Button("Load Model")
# Button to clone voice
clone_button = gr.Button("Clone Voice")
# Button to convert text to speech
tts_button = gr.Button("Convert Text to Speech")
# Load the model when the user uploads the .npz file
def load_and_initialize(npz):
cloner.load_model(npz.name) # Use the file path to load the model
cloner.load_tts_model() # Load the TTS model
return "Model Loaded!"
upload_button.click(fn=load_and_initialize, inputs=npz_file, outputs="text")
# Clone the voice when the button is pressed
clone_button.click(fn=cloner.clone_voice, inputs=audio_input, outputs=output_audio)
# Convert text to speech when the button is pressed
tts_button.click(fn=cloner.text_to_speech, inputs=text_input, outputs=output_audio)
return demo
if __name__ == "__main__":
demo = create_interface()
demo.launch()
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