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from TTS.api import TTS
import numpy as np
import torch
import os
import gradio as gr
from scipy.io.wavfile import write as write_wav
# Check if GPU is available
if torch.cuda.is_available():
device = "cuda"
else:
device = "cpu"
# Initialize the TTS object
tts = TTS(model_name="tts_models/multilingual/multi-dataset/xtts_v2", progress_bar=True)
tts.to(device) # Use GPU if available
# Function to list .wav files in the /clone/ folder
def list_wav_files():
clone_folder = "clone"
if not os.path.exists(clone_folder):
print(f"Error: Folder '{clone_folder}' not found.")
return []
wav_files = [f for f in os.listdir(clone_folder) if f.endswith(".wav")]
if not wav_files:
print(f"No .wav files found in '{clone_folder}'.")
return []
return wav_files
# Function to generate TTS audio and save it as a .wav file
def generate_tts_audio(text, voice_choice, speaker_name=None, wav_file_choice=None, uploaded_file=None, recorded_audio=None):
# Determine the reference audio file
if voice_choice == "existing_speaker":
if not speaker_name:
return "Error: Speaker name is required for existing speaker.", None
reference_audio = None
elif voice_choice == "voice_cloning":
if recorded_audio:
# Use the recorded audio for voice cloning
reference_audio = recorded_audio
elif uploaded_file:
# Use the uploaded file for voice cloning
reference_audio = uploaded_file
elif wav_file_choice:
# Use a file from the clone folder
wav_files = list_wav_files()
if not wav_files:
return "Error: No .wav files found for voice cloning.", None
try:
wav_file_index = int(wav_file_choice.split(":")[0].strip())
if wav_file_index < 0 or wav_file_index >= len(wav_files):
return "Error: Invalid .wav file index.", None
reference_audio = os.path.join("clone", wav_files[wav_file_index])
except (ValueError, IndexError, AttributeError):
return "Error: Invalid .wav file choice.", None
else:
return "Error: No reference audio provided for voice cloning.", None
else:
return "Error: Invalid voice choice.", None
# Generate TTS audio
if reference_audio:
# Use reference voice (voice cloning)
audio = tts.tts(
text=text,
speaker_wav=reference_audio,
language="en"
)
else:
# Use existing speaker
audio = tts.tts(
text=text,
speaker=speaker_name,
language="en"
)
# Convert audio to a NumPy array
audio_np = np.array(audio, dtype=np.float32)
# Save the audio as a .wav file
output_file = "output.wav"
write_wav(output_file, tts.synthesizer.output_sample_rate, audio_np)
return "Audio generated successfully!", (tts.synthesizer.output_sample_rate, audio_np)
# Gradio interface
def create_gradio_interface():
wav_files = list_wav_files()
wav_file_choices = [f"{i}: {file}" for i, file in enumerate(wav_files)]
with gr.Blocks() as demo:
gr.Markdown("# TTS Streaming System")
with gr.Row():
text_input = gr.Textbox(label="Enter text to generate speech", lines=3)
with gr.Row():
voice_choice = gr.Radio(choices=["existing_speaker", "voice_cloning"], label="Select voice type")
with gr.Row():
speaker_name = gr.Textbox(label="Enter the speaker name (e.g., 'Ana Florence')", visible=False)
wav_file_choice = gr.Dropdown(choices=wav_file_choices, label="Select a .wav file for cloning", visible=False)
uploaded_file = gr.Audio(label="Upload your own .wav file for cloning", type="filepath", visible=False)
recorded_audio = gr.Microphone(label="Record your voice for cloning", type="filepath", visible=False)
with gr.Row():
submit_button = gr.Button("Generate Speech")
with gr.Row():
output_text = gr.Textbox(label="Output", interactive=False)
output_audio = gr.Audio(label="Generated Audio", type="numpy", visible=True)
def update_components(choice):
if choice == "existing_speaker":
return gr.update(visible=True), gr.update(visible=False), gr.update(visible=False), gr.update(visible=False)
elif choice == "voice_cloning":
return gr.update(visible=False), gr.update(visible=True), gr.update(visible=True), gr.update(visible=True)
else:
return gr.update(visible=False), gr.update(visible=False), gr.update(visible=False), gr.update(visible=False)
voice_choice.change(update_components, inputs=voice_choice, outputs=[speaker_name, wav_file_choice, uploaded_file, recorded_audio])
submit_button.click(
generate_tts_audio,
inputs=[text_input, voice_choice, speaker_name, wav_file_choice, uploaded_file, recorded_audio],
outputs=[output_text, output_audio]
)
return demo
# Launch Gradio interface
if __name__ == "__main__":
demo = create_gradio_interface()
demo.launch(share=True) # Set share=True to create a public link |